spectrumAnalyzer

Display frequency spectrum of time-domain signals

Since R2022a

Description

The spectrumAnalyzer object displays frequency-domain signals and the frequency spectrum of time-domain signals. The scope shows the spectrum view and the spectrogram view. The object performs spectral estimation using the filter bank method and Welch's method of averaged modified periodograms. You can customize the spectrum analyzer display to show the data and the measurement information that you need. For more details, see Algorithms. The spectrum analyzer can display the power spectrum of the signal in three units, Watts, dBm, and dBW. For more information on how to convert the power within these three units, see Convert the Power Between Units.

To display the spectra of signals in the Spectrum Analyzer:

1. Create the spectrumAnalyzer object and set its properties.

2. Call the object with arguments, as if it were a function.

Creation

Syntax

scope = spectrumAnalyzer

scope = spectrumAnalyzer(Name=Value)

Description

scope = spectrumAnalyzer creates a spectrumAnalyzer object that displays the frequency spectrum of real or complex signals.

scope = spectrumAnalyzer(Name=Value) specifies nondefault properties for scope using one or more name-value arguments. For example, to display both spectrum and spectrogram, set ViewType to "spectrum-and-spectrogram".

Properties

Frequently Used

InputDomain — Domain of input signal

"time" (default) | "frequency"

The domain of the input signal you want to visualize, specified as "time" or "frequency". If you want to visualize time-domain signals, the Spectrum Analyzer transforms the signal to the frequency spectrum based on the algorithm you specify in the Method property.

Scope Window Use

In the Estimation tab on the Spectrum Analyzer toolstrip, set Input Domain to Time or Frequency.

Data Types: char | string

SpectrumType — Type of spectrum to display

"power" (default) | "power-density" | "rms"

The type of spectrum to display, specified as one of the following:

• "power" — Power spectrum.

• "power-density" — Power spectral density. The power spectral density is the squared magnitude of the spectrum normalized to a bandwidth of 1 hertz.

• "rms" — Root mean square. The root-mean-square shows the square root of the mean square. Use this option to view the frequency of voltage or current signals.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "time".

Scope Window Use

In the Analyzer tab on the Spectrum Analyzer toolstrip, click the drop down arrow of Spectrum to select Power, Power Density, or RMS.

To enable these options, set the Input Domain on the Estimation tab to Time.

Data Types: char | string

ViewType — View to display

"spectrum" (default) | "spectrogram" | "spectrum-and-spectrogram"

View to display, specified as one of the following:

• "spectrum" — Display frequency spectrum of signals.

• "spectrogram" — Display spectrogram of signals. Spectrogram shows the frequency content over time. Each line of the spectrogram is one periodogram. Time scrolls from the top to the bottom of the display. The most recent spectrogram update is at the top of the display.

• "spectrum-and-spectrogram" — Display both spectrum and spectrogram.

To learn more about how the Spectrum Analyzer computes spectrum and spectrogram, see the Algorithms section.

Tunable: Yes

Scope Window Use

In the Analyzer tab on the Spectrum Analyzer toolstrip, select Spectrum, Spectrogram, or both.

Data Types: char | string

SampleRate — Sample rate of input

10000 (default) | positive scalar

The sample rate of the input in Hz, specified as a positive scalar.

Tunable: Yes

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Bandwidth section, specify Sample Rate (Hz) to a finite scalar.

The Spectrum Analyzer shows the sample rate in the status bar at the bottom of the display.

Data Types: double

Method — Spectrum estimation method

"filter-bank" (default) | "welch"

Spectrum estimation method, specified as one of the following:

• "filter-bank" –– Use an analysis filter bank to estimate the power spectrum. Compared to Welch's method, this method has a lower noise floor, better frequency resolution, and lower spectral leakage and requires fewer samples per update.

• "welch" –– Use Welch's method of averaged modified periodograms.

For more details on these methods, see Algorithms.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "time".

Scope Window Use

In the Estimation tab of the Spectrum Analyzer toolstrip, set Method to Filter bank or Welch.

To enable this parameter, set Input Domain to Time in the Estimation tab.

Data Types: char | string

PlotAsTwoSidedSpectrum — Option to plot a two-sided spectrum

true (default) | false

Option to plot a two-sided spectrum, specified as one of the following:

• true — Compute and plot two-sided spectral estimates. When the input signal is complex valued, you must set this property to true.

• false — Compute and plot one-sided spectral estimates. If you set this property to false, then the input signal must be real valued.

  When you set this property to false, the Spectrum Analyzer uses power-folding. The y-axis values are twice the amplitude that they would be if you were to set this property to true, except at 0 and the Nyquist frequency. A one-sided power spectral density (PSD) contains the total power of the signal in the frequency interval from DC to half the Nyquist rate. For more information, see pwelch.

Tunable: Yes

Scope Window Use

Click the Spectrum tab or the Spectrogram tab (if enabled) of the Spectrum Analyzer toolstrip. In the Trace Options section, select Two-Sided Spectrum to compute and plot two-sided spectral estimates.

Data Types: logical

FrequencyScale — Scale to display frequency

"linear" (default) | "log"

Scale to display frequency, specified as one of the following:

• "linear" — Use a linear scale to display frequencies on the x-axis.

• "log" — Use a logarithmic scale to display frequencies on the x-axis.

Tunable: Yes

Dependency

To set this property to "log", set the PlotAsTwoSidedSpectrum property to false.

Scope Window Use

Click the Spectrum tab or the Spectrogram tab (if enabled) of the Spectrum Analyzer toolstrip. In the Scale section, set the Frequency Scale to Linear or Log.

To set the Frequency Scale to Log, clear the Two-Sided Spectrum check box in the Trace Options section in the Spectrum or the Spectrogram tab (if enabled). If you select the Two-Sided Spectrum check box, then you must set the Frequency Scale to Linear.

Data Types: char | string

PlotType — Plot type for normal traces

"line" (default) | "stem"

Type of plot to use for displaying normal traces, specified as "line" or "stem". Normal traces are traces that display free-running spectral estimates.

Tunable: Yes

Dependencies

To enable this property, set:

• ViewType to "spectrum" or "spectrum-and-spectrogram".

• PlotNormalTrace to true.

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip, navigate to the Configuration section and click Settings. In the Spectrum Analyzer Settings window that opens, under Display and Labels, set Plot Type to Line or Stem.

To enable the Plot Type, you must:

• Select Spectrum in the Views section of the Analyzer tab.

• Enable the Normal Trace check box in the Trace Options section of the Spectrum tab.

Data Types: char | string

AxesScaling — Axes scaling mode

"auto" (default) | "manual" | "onceatstop" | "updates"

Axes scaling mode, specified as one of the following:

• "auto" — The scope scales the axes to fit the data, both during and after simulation.

• "manual" — The scope does not scale the axes automatically.

• "onceatstop" — The scope scales the axes when the simulation stops and you call the release function.

• "updates" — The scope scales the axes after a specific number of visual updates. It determines the number of updates using the AxesScalingNumUpdates property.

Tunable: Yes

Data Types: char | string

AxesScalingNumUpdates — Number of updates before scaling

100 (default) | positive integer

Number of updates before scaling, specified as a positive integer.

Tunable: Yes

Dependency

To enable this property, set AxesScaling to "updates".

Data Types: double

Advanced

RBWSource — Source of resolution bandwidth value

"auto" (default) | "property"

The source of the resolution bandwidth (RBW), specified as "auto" or "property".

• "auto" — The Spectrum Analyzer adjusts the spectral estimation resolution to ensure that there are 1024 RBW intervals over the defined frequency span.

• "property" — Specify the resolution bandwidth directly using the RBW property.

Tunable: Yes

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Bandwidth section, set RBW (Hz) to either Auto or a positive scalar.

Data Types: char | string

RBW — Resolution bandwidth

9.76 (default) | positive scalar

Resolution bandwidth (RBW) in Hz, specified as a positive scalar. Specify the value to ensure that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW satisfies this condition:

$$\frac{span}{RBW}>2$$

Specify the overall span based on how you set the FrequencySpan property.

RBW controls the spectral resolution of the displayed signal. The RBW value determines the spacing between frequencies that can be resolved. A smaller value gives a higher spectral resolution and lowers the noise floor. That is, the Spectrum Analyzer can resolve frequencies that are closer to each other. However, this comes at the cost of a longer sweep time.

Tunable: Yes

Dependency

To enable this property, set RBWSource to "property".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Bandwidth section, set RBW (Hz) to a positive scalar.

The Spectrum Analyzer shows the value of RBW in the status bar at the bottom of the display.

Data Types: double

FilterSharpness — Sharpness of lowpass filter

0.3 (default) | nonnegative scalar in the range [0,1]

Sharpness of the prototype lowpass filter, specified as a real nonnegative scalar in the range [0,1].

Increasing the filter sharpness decreases the spectral leakage and gives a more accurate power reading.

Tunable: Yes

Dependencies

To enable this property, set Method to "filter-bank".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Frequency Resolution section, move the Sharpness slider.

To enable this parameter, set Input Domain to Time in the Estimation tab.

Data Types: double

FrequencyVectorSource — Source of frequency vector

"auto" (default) | "property"

Source of the frequency vector, specified as one of the following:

• "auto" — The Spectrum Analyzer computes the frequency vector based on the frame size of the input signal and the specified sample rate.

• "property" — Enter a custom vector in the FrequencyVector property.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "frequency".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Domain section, set Frequency (Hz) to either Auto or a monotonically increasing vector of length equal to the input signal frame size.

To enable the Frequency (Hz), set Input Domain to Frequency.

Data Types: char | string

FrequencyVector — Custom frequency vector

[-5000 5000] (default) | monotonically increasing vector

Custom frequency vector, specified as a monotonically increasing vector. This vector determines the x-axis of the display. The vector must be monotonically increasing and must have the same length as the input signal frame size.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "frequency".

• FrequencyVectorSource to "property".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Domain section, set Frequency (Hz) to either Auto or a monotonically increasing vector of length equal to the input signal frame size.

To enable the Frequency (Hz), set Input Domain to Frequency.

Data Types: double

FrequencySpan — Frequency span mode

"full" (default) | "span-and-center-frequency" | "start-and-stop-frequencies"

Frequency span mode, specified as one of the following:

• "full" –– The Spectrum Analyzer computes and plots the spectrum over the entire Nyquist Frequency Interval.

• "span-and-center-frequency" –– The Spectrum Analyzer computes and plots the spectrum over the interval specified by the Span and CenterFrequency properties.

• "start-and-stop-frequencies" –– The Spectrum Analyzer computes and plots the spectrum over the interval specified by the StartFrequency and StopFrequency properties.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "time".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Frequency Options section, set Frequency Span to Full, Span and Center Frequency, or Start and Stop Frequencies.

To enable the Frequency Span, set Input Domain to Time.

Data Types: char | string

Span — Frequency span to compute spectrum

10e3 (default) | real positive scalar

Frequency span over which the Spectrum Analyzer computes and plots the spectrum, specified as a positive scalar in Hz. The overall span, defined by this property and the CenterFrequency property, must fall within the Nyquist Frequency Interval.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• FrequencySpan to "span-and-center-frequency"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Frequency Options section, set Frequency Span to Span and Center Frequency and Span (Hz) to a positive scalar.

To enable the Frequency Span, set Input Domain to Time.

Data Types: double

CenterFrequency — Center of frequency span

0 (default) | real scalar

Center of frequency span over which the Spectrum Analyzer computes and plots the spectrum, specified as a real scalar in Hz. The overall frequency span, defined by Span and this property, must fall within the Nyquist Frequency Interval.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• FrequencySpan to "span-and-center-frequency"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Frequency Options section, set Frequency Span to Span and Center Frequency and Center Frequency (Hz) to a real scalar.

To enable the Frequency Span, set Input Domain to Time.

Data Types: double

StartFrequency — Starting frequency in frequency interval

-5e3 (default) | real scalar

Starting frequency in the frequency interval over which the Spectrum Analyzer computes and plots the spectrum, specified as a real scalar in Hz. The overall span, which is defined by this property and StopFrequency, must fall within the Nyquist Frequency Interval.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• FrequencySpan to "start-and-stop-frequencies"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Frequency Options section, set Frequency Span to Start and Stop Frequencies and Start Frequency (Hz) to a real scalar.

To enable the Frequency Span, set Input Domain to Time.

Data Types: double

StopFrequency — Ending frequency in frequency interval

5e3 (default) | real scalar

Ending frequency in the frequency interval over which the Spectrum Analyzer computes and plots the spectrum, specified as a real scalar in Hz. The overall span, which is defined by this property and the StartFrequency property, must fall within the Nyquist Frequency Interval.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• FrequencySpan to "start-and-stop-frequencies"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Frequency Options section, set Frequency Span to Start and Stop Frequencies and Stop Frequency (Hz) to a real scalar.

To enable the Frequency Span, set Input Domain to Time.

Data Types: double

OverlapPercent — Percentage of overlap

0 (default) | scalar in the range [0 100)

Percentage of overlap between the previous and current buffered data segments, specified as a scalar in the range [0 100). The overlap creates a window segment that the object uses to compute a spectral estimate.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• Method to "welch"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Window Options section, set the Overlap (%).

To enable the Overlap (%), set Input Domain to Time and Method to Welch in the Estimation tab on the Spectrum Analyzer toolstrip.

Data Types: double

Window — Window function

"hann" (default) | "blackman-harris" | "chebyshev" | "custom" | "flat-top" | "hamming" | "kaiser" | "rectangular"

Window function, specified as one of the following preset windows. For more information on a window option, click the link to the corresponding function.

Window Option	Corresponding Signal Processing Toolbox™ Function
"hann"	hann
"blackman-harris"	blackmanharris
"chebyshev"	chebwin
"flat-top"	flattopwin
"hamming"	hamming
"kaiser"	kaiser
"rectangular"	rectwin

To use your own spectral estimation window, set this property to "custom" and specify a custom window function in the CustomWindow property.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• Method to "welch"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Window Options section, set the Window.

To enable the Window, set Input Domain to Time and Method to Welch in the Estimation tab on the Spectrum Analyzer toolstrip.

Data Types: char | string

CustomWindow — Name of custom window function

"hann" (default) | character array | string scalar

Name of custom window function, specified as a character array or string scalar. The custom window function name must be on the MATLAB^® path. Use this property to customize a window function using additional properties available with the Signal Processing Toolbox.

Tunable: Yes

Example:

Define and use a custom window function.

function w = my_hann(L)
    w = hann(L,"periodic")
end

scope.Window = "custom";
scope.CustomWindow = "my_hann"

Dependency

To use this property, set Window to "custom".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Window Options section, for the Window, enter a custom window function name.

Data Types: char | string

SidelobeAttenuation — Sidelobe attenuation of window

60 (default) | scalar greater than or equal to 45

Sidelobe attenuation of the window in decibels (dB), specified as a positive scalar greater than or equal to 45.

Tunable: Yes

Dependency

To enable this property, set Window to "chebyshev" or "kaiser".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Window Options section, set the Attenuation (dB).

To enable the Attenuation (dB), set:

• Input Domain to Time

• Method to Welch

• Window to either Chebyshev or Kaiser in the Estimation tab on the Spectrum Analyzer toolstrip.

Data Types: double

AveragingMethod — Averaging method

"vbw" (default) | "exponential"

Averaging method, specified as one of the following:

• "vbw" — Video bandwidth method. The object uses a lowpass filter to smooth the trace and decrease noise. Use the VBWSource and VBW properties to specify the VBW value.

• "exponential" — Weighted average of samples. The object computes the average over samples weighted by an exponentially decaying forgetting factor. Use the ForgettingFactor property to specify the weighted forgetting factor.

For more information on averaging methods, see Averaging Method.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "time".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Averaging section, set Averaging Method to VBW or Exponential.

To enable the Averaging Method, set Input Domain to Time.

Data Types: char | string

ForgettingFactor — Forgetting factor of weighted average method

0.9 (default) | scalar in the range [0,1]

Forgetting factor of the exponential weighted averaging method, specified as a scalar in the range [0,1].

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time".

• AveragingMethod to "exponential"

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Averaging section, adjust the slider for Forgetting Factor.

To enable the Forgetting Factor, set Input Domain to Time and Averaging Method to Exponential.

Data Types: double

VBWSource — Source of video bandwidth

"auto" (default) | "property"

Source of the video bandwidth (VBW), specified as either "auto" or "property".

• "auto" — The Spectrum Analyzer adjusts the VBW such that the equivalent forgetting factor is 0.9.

• "property" — The Spectrum Analyzer adjusts the VBW using the value specified in the VBW property.

For more details on the video bandwidth method, see Averaging Method.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "time" and AveragingMethod to "vbw".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Averaging section, set VBW (Hz) to either Auto or a positive real scalar less than or equal to Sample Rate (Hz)/2.

To enable the VBW (Hz), set Input Domain to Time and Averaging Method to VBW.

Data Types: char | string

VBW — Video bandwidth

10 (default) | positive scalar

Video bandwidth, specified as a positive scalar less than or equal to SampleRate/2. For more details on the video bandwidth method, see Averaging Method.

The Spectrum Analyzer shows the value of VBW in the status bar at the bottom of the display.

Tunable: Yes

Dependency

To enable this property, set VBWSource to "property".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Averaging section, set VBW (Hz) to either Auto or enter a positive real scalar that is less than or equal to Sample Rate (Hz)/2.

To enable the VBW (Hz), set Input Domain to Time and Averaging Method to VBW.

Data Types: double

InputUnits — Units of frequency input

"dBm" (default) | "dBV" | "dBW" | "Vrms" | "Watts" | "none"

Units of the frequency-domain input, specified as "dBm", "dBV", "dBW", "Vrms", "Watts", or "none". The Spectrum Analyzer scales frequency data according to the specified display unit.

Tunable: Yes

Dependency

To enable this property, set InputDomain to "frequency".

Scope Window Use

Click the Estimation tab on the Spectrum Analyzer toolstrip. In the Domain section, set Input Unit.

To enable the Input Unit, set Input Domain to Frequency.

Data Types: char | string

SpectrumUnits — Units of the spectrum

"dBm" (default) | "dBFS" | "dBV" | "dBW" | "Vrms" | "Watts" | "dBm/Hz" | "dBW/Hz" | "dBFS/Hz" | "Watts/Hz" | "auto"

Units in which the Spectrum Analyzer displays power values, specified as one of the following:

• "dBm"

• "dBFS"

• "dBV"

• "dBW"

• "Vrms"

• "Watts"

• "dBm/Hz"

• "dBW/Hz"

• "dBFS/Hz"

• "Watts/Hz"

• "auto"

Tunable: Yes

Dependency

The spectrum units available depend on the value you specify in the SpectrumType property.

InputDomain	SpectrumType	Allowed SpectrumUnits
"time"	"power"	"dBm", "dBW", "dBFS", "Watts"
	"power-density"	"dBm/Hz", "dBW/Hz","dBFS/Hz", "Watts/Hz"
	"rms"	"dBV", "Vrms"
"frequency"	―	"auto", "dBm", "dBV", "dBW", "Vrms", "Watts"

If you set the InputDomain property to "frequency" and the SpectrumUnits property to "auto", the Spectrum Analyzer assumes the spectrum units to be equal to input units specified in the InputUnits property. If you set InputDomain to "time" and SpectrumUnits to any option other than "auto", the Spectrum Analyzer converts the units specified in InputUnits to the units specified in SpectrumUnits.

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip. In the Scale section, set Spectrum Unit.

Data Types: char | string

FullScaleSource — Source of full-scale value

"auto" (default) | "property"

Source of the dBFS scaling factor, specified as either "auto" or "property".

• "auto" –– The Spectrum Analyzer adjusts the scaling factor based on the input data.

• "property" –– Specify the full-scale scaling factor using the FullScale property.

Tunable: Yes

Dependency

To enable this property, set:

• InputDomain to "time"

• SpectrumType to "power" or "power-density"

• SpectrumUnits to "dBFS" or "dBFS/Hz"

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip. In the Scale section, set the Full Scale to either Auto or a positive scalar.

To enable the Full Scale:

• In the Analyzer tab, set the spectrum type to Power or Power Density.

• In the Estimation tab, set Input Domain to Time.

• In the Spectrum tab, set Spectrum Unit to dBFS or dBFS/Hz (when spectrum type is set to Power Density).

Data Types: char | string

FullScale — dBFS full scale

1 (default) | positive scalar

dBFS full scale, specified a positive scalar.

Tunable: Yes

Dependency

To enable this property, set:

1. InputDomain to "time"

2. SpectrumType to "power" or "power-density"

3. SpectrumUnits to "dBFS" or "dBFS/Hz"

4. FullScaleSource to "property"

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip. In the Scale section, set the Full Scale to either Auto or enter a positive scalar.

To enable the Full Scale:

• In the Analyzer tab, set the spectrum type to Power or Power Density.

• In the Estimation tab, set Input Domain to Time.

• In the Spectrum tab, set Spectrum Unit to dBFS or dBFS/Hz (when spectrum type is set to Power Density).

Data Types: double

ReferenceLoad — Reference load to compute power levels

1 (default) | positive scalar

Load that the scope uses as a reference to compute power levels, specified as a positive scalar in Ohms.

Tunable: Yes

Dependency

To enable this property, set:

• SpectrumType to "power" or "power-density".

• SpectrumUnits to any option other than "dBFS" or "dBFS/Hz".

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip. In the Scale section, set Reference Load (Ω).

Data Types: double

FrequencyOffset — Offset to apply to frequency axis

0 (default) | scalar | vector

Offset to apply to the frequency axis (x-axis) in units of Hz, specified as one of the following:

• Scalar — Apply the same frequency offset to all channels.

• Vector — Apply a specific frequency offset for each channel. The vector length must be equal to the number of input channels.

  The overall span must fall within the Nyquist Frequency Interval. You can control the overall span in different ways based on how you set the FrequencySpan property.

Tunable: Yes

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Bandwidth section, set Offset (Hz).

Data Types: double

Spectrogram

SpectrogramChannel — Channel for which spectrogram is plotted

1 (default) | positive integer

Channel for which the spectrogram is plotted, specified as a positive integer in the range [1 N], where N is the number of input channels.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrogram" or "spectrum-and-spectrogram".

Scope Window Use

Click the Spectrogram tab on the Spectrum Analyzer toolstrip. In the Channel section, select a Channel.

Data Types: double

TimeResolutionSource — Source of the time resolution

"auto" (default) | "property"

Source of the time resolution of each spectrogram line, specified as either "auto" or "property".

When you set RBWSource and TimeResolutionSource to "auto", then RBW is set such that there are 1024 RBW intervals in one frequency span. The time resolution is set to 1/RBW.

When RBWSource is set to "auto" and TimeResolutionSource is set to "property", then time resolution becomes the main control and RBW is set to 1/TimeResolution Hz.

When RBWSource is set to "property" and TimeResolutionSource is set to "auto", then RBW becomes the main control and the time resolution is set 1/RBW s.

When both RBWSource and TimeResolutionSource are set to "property", then the specified time resolution value must be equal to or larger than the minimum attainable time resolution which is defined by 1/RBW. Several spectral estimates are combined into one spectrogram line to obtain the desired time resolution.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrogram" or "spectrum-and-spectrogram".

Scope Window Use

Click the Spectrogram tab on the Spectrum Analyzer toolstrip. In the Time Options section, set the Time Resolution (s) to Auto or enter a positive scalar.

To enable the Time Resolution (s), select Spectrogram in the Analyzer tab.

Data Types: char | string

TimeResolution — Time resolution of each spectrogram line

0.001 (default) | positive scalar

Time resolution of each spectrogram line in seconds, specified as a positive scalar.

Tunable: Yes

Dependency

To enable this property, set:

• ViewType to "spectrogram" or "spectrum-and-spectrogram"

• TimeResolutionSource to "property".

Scope Window Use

Click the Spectrogram tab on the Spectrum Analyzer toolstrip. In the Time Options section, set the Time Resolution (s) to Auto or enter a positive scalar.

To enable the Time Resolution (s), select Spectrogram in the Analyzer tab.

Data Types: double

TimeSpanSource — Source of time span value

"auto" (default) | "property"

Source for the time span of the spectrogram, specified as either one of these:

• "auto" –– The spectrogram displays 100 spectrogram lines at any given time.

• "property" –– The spectrogram uses the time duration you specify in seconds in the TimeSpan property.

  The time span that you specify must be at least two times larger than the duration of the number of samples required for a spectral update.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrogram" or "spectrum-and-spectrogram".

Scope Window Use

Click the Spectrogram tab on the Spectrum Analyzer toolstrip. In the Time Options section, set the Time Span (s) to Auto or enter a positive scalar.

Data Types: char | string

TimeSpan — Time span of spectrogram

0.1 (default) | positive scalar

Time span of the spectrogram display in seconds, specified as a positive scalar. You must set the time span to be at least twice as large as the duration of the number of samples required for a spectral update.

Tunable: Yes

Dependency

To enable this property, set:

• ViewType to "spectrogram" or "spectrum-and-spectrogram".

• TimeSpanSource to "property".

Scope Window Use

Click the Spectrogram tab on the Spectrum Analyzer toolstrip. In the Time Options section, set the Time Span (s) to Auto or enter a positive scalar.

Data Types: double

Measurements

MeasurementChannel — Channel for which to obtain measurements

1 (default) | positive integer

The channel for which you need to obtain measurements, specified as a positive integer in the range [1 N], where N is the number of input channels.

Tunable: Yes

Scope Window Use

Click the Measurements tab on the Spectrum Analyzer toolstrip. In the Channel section, select a Channel.

Data Types: double

ChannelMeasurements — Channel measurements

ChannelMeasurementsConfiguration object

Channel measurements, specified as a ChannelMeasurementsConfiguration object. Enable channel measurements to compute and display the occupied bandwidth or adjacent channel power ratio. All ChannelMeasurementsConfiguration properties are tunable.

Tunable: Yes

Dependency

To enable this property, set ViewType to either "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Channel Measurements tab on the Spectrum Analyzer toolstrip and modify the measurement settings.

The Channel Measurements tab appears when you select Spectrum in the Analyzer tab.

CursorMeasurements — Cursor measurements

CursorMeasurementsConfiguration object

Cursor measurements, specified as a CursorMeasurementsConfiguration object. Enable cursor measurements to display waveform cursors. All CursorMeasurementsConfiguration properties are tunable.

Tunable: Yes

Scope Window Use

Click the Measurements tab on the Spectrum Analyzer toolstrip and modify the cursor measurements in the Cursors section.

DistortionMeasurements — Distortion measurements

DistortionMeasurementsConfiguration object

Distortion measurements, specified as a DistortionMeasurementsConfiguration object. Enable distortion measurements to compute and display the harmonic distortion and intermodulation distortion. All DistortionMeasurementsConfiguration properties are tunable. For more details, see Distortion Measurements and Harmonic Measurements.

Tunable: Yes

Dependency

To enable this property, set ViewType to either "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Measurements tab on the Spectrum Analyzer toolstrip and modify the distortion measurements in the Distortion section.

The Measurements tab appears when you select Spectrum in the Analyzer tab.

PeakFinder — Peak finder measurement

PeakFinderConfiguration object

Peak finder measurement, specified as a PeakFinderConfiguration object. Enable peak finder to compute and display the largest calculated peak values. All PeakFinderConfiguration properties are tunable.

Tunable: Yes

Dependency

To enable this property, set ViewType to either "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Measurements tab on the Spectrum Analyzer toolstrip and modify the peak finder measurements in the Peaks section.

The Measurements tab appears when you select Spectrum in the Analyzer tab.

SpectralMask — Spectral mask configuration

SpectralMaskConfiguration object

Spectral mask configuration, specified as a SpectralMaskConfiguration object. Use the spectral mask configuration to draw upper and lower or upper or lower mask lines in the power and power-density plots. All SpectralMaskConfiguration properties are tunable.

Tunable: Yes

Dependency

To enable this property, set:

• ViewType to either "spectrum" or "spectrum-and-spectrogram".

• SpectrumType to either "power" or "power-density".

Scope Window Use

Click the Spectral Mask tab on the Spectrum Analyzer toolstrip and modify the settings.

The Spectral Mask tab appears when you:

• Select Spectrum in the Analyzer tab.

• In the drop-down list under Spectrum, choose either Power or Power Density.

Visualization

Name — Caption to display in spectrum Analyzer window

"Spectrum Analyzer" (default) | character vector | string scalar

Caption to display in the scope window, specified as a character vector or string scalar.

Tunable: Yes

Data Types: char | string

Position — Spectrum Analyzer window position in pixels

[left bottom 800 500] (default) | [left bottom width height]

Spectrum Analyzer window position in pixels, specified as a four-element double vector of the form [left bottom width height]. You can place the scope window in a specific position on your screen by modifying the values of this property.

By default, the window appears at the center of your screen with a width of 800 pixels and height of 500 pixels. The exact center coordinates depend on your screen resolution.

Tunable: Yes

MaximizeAxes — Maximize axes control

"auto" (default) | "on" | "off"

Maximize axes control, specified as one of the following:

• "auto" –– The Spectrum Analyzer maximizes axes only if the display does not contain any labels or title annotations.

• "on" –– The Spectrum Analyzer maximizes axes in all displays.

• "off" –– The Spectrum Analyzer does not maximize axes in any display.

Tunable: Yes

Data Types: char | string

PlotNormalTrace — Option to plot normal trace

true (default) | false

To remove normal traces from the display, set this property to false. These traces display the free-running spectral estimates. The Spectrum Analyzer continues its spectral computations even when you set this property to false.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip and select the Normal Trace check box in the Trace Options section.

To enable the Normal Trace check box, select Spectrum in the Analyzer tab.

Data Types: logical

PlotMaxHoldTrace — Option to plot max-hold trace

false (default) | true

Option to plot max-hold trace, specified as true or false. To compute and plot the maximum-hold spectrum of each input channel, set this property to true. The Spectrum Analyzer computes the maximum-hold spectrum at each frequency bin by keeping the maximum value of all the power spectrum estimates. When you change the value of this property, the Spectrum Analyzer resets its maximum-hold computations.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip and select the Max-Hold Trace check box in the Trace Options section.

To enable the Max-Hold Trace check box, select Spectrum in the Analyzer tab.

Data Types: logical

PlotMinHoldTrace — Option to plot min-hold trace

false (default) | true

Option to plot min-hold trace, specified as true or false. To compute and plot the minimum-hold spectrum of each input channel, set this property to true. The Spectrum Analyzer computes the minimum-hold spectrum at each frequency bin by keeping the minimum value of all the power spectrum estimates. When you change the value of this property, the Spectrum Analyzer resets its minimum-hold computations.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Spectrum tab on the Spectrum Analyzer toolstrip and select the Min-Hold Trace check box in the Trace Options section.

To enable the Min-Hold Trace check box, select Spectrum in the Analyzer tab.

Data Types: logical

Title — Display title

'' (default) | character vector | string scalar

Display title, specified as a character vector or a string scalar.

Tunable: Yes

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Configuration section, click Settings. In the Spectrum Analyzer Settings window that opens up, under Display and labels, enter Title.

Data Types: char | string

YLabel — y-axis label

'' (default) | character vector | string scalar

y-axis label, specified as a character vector or a string scalar. The Spectrum Analyzer displays the label to the left of the y-axis.

Regardless of this property, Spectrum Analyzer always displays power units as one of the SpectrumUnits values.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Configuration section, click Settings. In the Spectrum Analyzer Settings window that opens up, under Display and labels, enter Y-Label.

To enable the Y-Label, select Spectrum in the Analyzer tab.

Data Types: char | string

YLimits — y-axis limits

[-80, 20] (default) | [ymin ymax]

y-axis limits, specified as a two-element numeric vector of the form [ymin ymax]. The units of the y-axis limits depend on the SpectrumUnits property.

Example: scope.YLimits = [-10,20]

Tunable: Yes

Dependencies

To enable this property, set the ViewType property to "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Configuration section, click Settings. In the Spectrum Analyzer Settings window that opens up, under Display and Labels, enter Y-Axis Limits.

To enable the Y-Axis Limits, select Spectrum in the Analyzer tab.

ColorLimits — Color limits of spectrogram

[-80, 20] (default) | [colorMin colorMax]

Color limits of the spectrogram, specified as a two-element numeric vector of the form [colorMin colorMax]. The units of the color limits directly depend upon the SpectrumUnits property.

Example: scope.ColorLimits = [-10,20]

Tunable: Yes

Dependencies

To enable this property, set the ViewType property to "spectrogram" or "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Configuration section, click Settings. In the Spectrum Analyzer Settings window that opens up, under Display and Labels, enter Color Limits.

To enable the Color Limits, select Spectrogram in the Analyzer tab.

Colormap — Color look-up table

"jet" (default) | "bone" | "cool" | "copper" | "gray" | "hot" | "parula" | three-column matrix

Color look-up table, specified as a valid colormap name or a three-column matrix with values in the range [0,1] defining RGB triplets.

Tunable: Yes

Dependencies

To enable this property, set the ViewType property to "spectrogram" or "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Configuration section, click Settings. In the Spectrum Analyzer Settings window that opens up, under Display and Labels, enter Color Map.

To enable the Color Map, select Spectrogram in the Analyzer tab.

Data Types: double | char | string

ShowGrid — Flag to show grid

true (default) | false

Flag to show the grid, specified as true or false. Set this property to true to show grid lines in the plot.

Tunable: Yes

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. In the Configuration section, click Settings. In the Spectrum Analyzer Settings window that appears, under Display and Labels, select Show Grid.

Data Types: logical

ShowLegend — Show or hide legend

false (default) | true

Show or hide the legend, specified as true or false. To show a legend with the input names, set this property to true.

Use the legend to control which signals are visible. In the scope legend, click a signal name to hide the signal in the scope. To show the signal, click the signal name again. To show only one signal, right-click the signal name. To show all signals, press Esc.

Tunable: Yes

Dependencies

To enable this property, set the ViewType property to "spectrum" or "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. To see the legend, click Legend in the Configuration section.

To enable the Legend, select Spectrum in the Analyzer tab.

Data Types: logical

ShowColorbar — Show or hide color bar

true (default) | false

Show or hide color bar, specified as true or false.

Tunable: Yes

Dependencies

To enable this property, set the ViewType property to "spectrogram" or "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. To see the color bar, click Colorbar in the Configuration section.

To enable the Colorbar, select Spectrogram in the Analyzer tab.

Data Types: logical

ChannelNames — Channel names

empty cell (default) | cell array of character vectors | array of strings

Channel names in the input data, specified as a cell array of character vectors or an array of strings. The names you specify in this property appear in the following locations:

• Legend

• Spectrum Analyzer Settings > Color and styling section

• Measurements and Channel Measurements tabs

If you do not specify channel names, the Spectrum Analyzer names the channels as Channel 1, Channel 2, and so on.

Tunable: Yes

Dependency

To see the channel names, set ShowLegend to true.

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. To see the legend, click Legend in the Configuration section.

Data Types: char

AxesLayout — Layout of axes

"vertical" (default) | "horizontal"

Layout of the axes, specified as one of "vertical" or "horizontal". A vertical layout stacks the spectrum above the spectrogram. A horizontal layout puts the two views side-by-side.

Tunable: Yes

Dependency

To enable this property, set ViewType to "spectrum-and-spectrogram".

Scope Window Use

Click the Analyzer tab on the Spectrum Analyzer toolstrip. Select Spectrum and Spectrogram. In the Configuration section, select and update Layout.

Data Types: char | string

Usage

Syntax

scope(signal)

scope(signal1,signal2,...,signalN)

Description

scope(signal) displays the frequency spectrum of the time-domain signal in the Spectrum Analyzer. If signal is a frequency-domain signal, the signal is displayed directly in the Spectrum Analyzer.

scope(signal1,signal2,...,signalN) displays the frequency spectrum of multiple signals in the Spectrum Analyzer. The number of channels in each signal can be different but the frame size of each signal should be the same.

Input Arguments

signal — Input signal or signals to visualize

scalar | vector | matrix

Input signal or signals to visualize, specified as a scalar, vector, or a matrix. The number of channels in each signal can be different but the frame size of each signal should be the same.

This scope supports variable-size input signals. That is, the frame size (number of rows) of the input signals can change during simulation, but the number of channels (number of columns) cannot change.

When you set the InputDomain property to "time", the input signals can be real or complex. When you set the InputDomain property to "frequency", the input signals must be real.

Example: scope(signal1,signal2)

Scope Window Use

To change the appearance of signals in the Spectrum Analyzer, click the Analyzer tab and then click Settings. In the Spectrum Analyzer Settings window, under Color and styling, select a signal and modify its style, width, color, and marker type.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fi
Complex Number Support: Yes

Object Functions

Specific to spectrumAnalyzer

generateScript	Generate MATLAB script to create scope with current settings
getMeasurementsData	Get the current measurement data displayed on the spectrum analyzer
getSpectralMaskStatus	Get test results of current spectral mask
getSpectrumData	Save spectrum data shown in spectrum analyzer
isNewDataReady	Check spectrum analyzer for new data

Specific to Scopes

show	Display scope window
hide	Hide scope window
isVisible	Determine visibility of scope

Common to All System Objects

step	Run System object algorithm
release	Release resources and allow changes to System object property values and input characteristics
reset	Reset internal states of System object

Note

If you want to restart the simulation from the beginning, call reset to clear the scope window display. Do not call reset after calling release.

Examples

Spectrum Analyzer for One-Sided Power Spectrum

View a one-sided power spectrum made from the sum of fixed real sine waves with different amplitudes and frequencies.

Fs = 100e6;  % Sample rate
fSz = 5000;  % Frame size

sin1 = dsp.SineWave(1e0,5e6,0,SamplesPerFrame=fSz,SampleRate=Fs);
sin2 = dsp.SineWave(1e-1,15e6,0,SamplesPerFrame=fSz,SampleRate=Fs);
sin3 = dsp.SineWave(1e-2,25e6,0,SamplesPerFrame=fSz,SampleRate=Fs);
sin4 = dsp.SineWave(1e-3,35e6,0,SamplesPerFrame=fSz,SampleRate=Fs);
sin5 = dsp.SineWave(1e-4,45e6,0,SamplesPerFrame=fSz,SampleRate=Fs);

scope = spectrumAnalyzer(SampleRate=Fs,AveragingMethod="exponential",...
    PlotAsTwoSidedSpectrum=false,...
    RBWSource="auto",SpectrumUnits="dBW");
    
for idx = 1:250
     y1 = sin1();
     y2 = sin2();
     y3 = sin3();
     y4 = sin4();
     y5 = sin5();
     scope(y1+y2+y3+y4+y5+0.0001*randn(fSz,1));
end

Call the release function to let property values and input characteristics change. The scope automatically scales the axes.

release(scope)

Run the clear function to close the Spectrum Analyzer window.

clear('scope');

Spectrum Analyzer For Two-Sided Power Spectrum

View a two-sided power spectrum of a noisy sine wave on the Spectrum Analyzer.

sin = dsp.SineWave(Frequency=100,SampleRate=1000,...
    SamplesPerFrame=1000);
scope = spectrumAnalyzer(SampleRate=sin.SampleRate);
for ii = 1:250
  x = sin() + 0.05*randn(1000,1);
  scope(x);
end

Call the release function to change property values and input characteristics. The scope automatically scales the axes and updates the display one more time if the internal buffer contains any more data.

release(scope);

Run the MATLAB clear function to close the Spectrum Analyzer window.

clear('scope');

Spectrogram of Chirp Signal

Plot the spectrogram for a chirp signal with added random noise.

Fs = 233e3;
frameSize = 20e3;
chirp = dsp.Chirp(SampleRate=Fs,SamplesPerFrame=frameSize,...
  InitialFrequency=11e3,TargetFrequency=11e3+55e3);
  
scope = spectrumAnalyzer(SampleRate=Fs,...
    AveragingMethod="exponential",...
    ForgettingFactor=0.3,ViewType="spectrogram",...
    RBWSource="property",RBW=500,...
    TimeSpanSource="property",TimeSpan=2);

scope.PlotAsTwoSidedSpectrum = false;

for idx = 1:50
  y = chirp()+0.05*randn(frameSize,1);  
  scope(y);
end
release(scope)

Display Frequency Input from Spectral Estimation

Use the Spectrum Analyzer to display frequency input from spectral estimates of sinusoids embedded in white Gaussian noise.

Initialization

Create two dsp.SpectrumEstimator objects. Set one object to use the Welch-based spectral estimation technique with a Hann window. Set the other object to use the filter bank estimation. Specify a noisy sine wave input signal with four sinusoids at 0.16, 0.2, 0.205, and 0.25 cycles per sample. View the spectral estimate using the spectrumAnalyzer object.

FrameSize = 420;
Fs = 1;
Frequency = [0.16 0.2 0.205 0.25];
sinegen = dsp.SineWave(SampleRate=Fs,SamplesPerFrame=FrameSize,...
    Frequency=Frequency,Amplitude=[2e-5 1  0.05  0.5]);
NoiseVar = 1e-10;
numAvgs = 8;

hannEstimator = dsp.SpectrumEstimator(PowerUnits="dBm",...
    Window="Hann",FrequencyRange="onesided",...
    SpectralAverages=numAvgs,SampleRate=Fs);

filterBankEstimator = dsp.SpectrumEstimator(PowerUnits="dBm",...
    Method="Filter bank",FrequencyRange="onesided",...
    SpectralAverages=numAvgs,SampleRate=Fs);

spectrumPlotter = spectrumAnalyzer(InputDomain="frequency",...
    SampleRate=Fs,SpectrumUnits="dBm",...
    YLimits=[-120,40],PlotAsTwoSidedSpectrum=false,...
    ChannelNames={'Hann window','Filter bank'},ShowLegend=true);

Streaming

Stream the input. Compare the spectral estimates in the spectrum analyzer.

for i = 1:1000
    x = sum(sinegen(),2) + sqrt(NoiseVar)*randn(FrameSize,1);
    Pse_hann = hannEstimator(x);
    Pfb = filterBankEstimator(x);
    spectrumPlotter([Pse_hann,Pfb])
end

Obtain Measurements Data Programmatically for spectrumAnalyzer object

Compute and display the power spectrum of a noisy sinusoidal input signal using the spectrumAnalyzer MATLAB® object. Measure the peaks, cursor placements, adjacent channel power ratio, and distortion values in the spectrum by enabling these properties:

• PeakFinder

• CursorMeasurements

• ChannelMeasurements

• DistortionMeasurements

Initialization

The input sine wave has two frequencies: 1000 Hz and 5000 Hz. Create two dsp.SineWave System objects to generate these two frequencies. Create a spectrumAnalyzer object to compute and display the power spectrum.

Fs = 44100;
Sineobject1 = dsp.SineWave(SamplesPerFrame=1024,PhaseOffset=10,...
    SampleRate=Fs,Frequency=1000);
Sineobject2 = dsp.SineWave(SamplesPerFrame=1024,...
    SampleRate=Fs,Frequency=5000);
SA = spectrumAnalyzer(SampleRate=Fs,SpectrumType="power",...
    PlotAsTwoSidedSpectrum=false,ChannelNames={'Power spectrum of the input'},...
    YLimits=[-120 40],ShowLegend=true);

Enable Measurements Data

To obtain the measurements, set the Enabled property to true.

SA.CursorMeasurements.Enabled = true;
SA.ChannelMeasurements.Enabled = true;
SA.PeakFinder.Enabled = true;
SA.DistortionMeasurements.Enabled = true;

Use getMeasurementsData

Stream in the noisy sine wave input signal and estimate the power spectrum of the signal using the spectrumAnalyzer object. Measure the characteristics of the spectrum. Use the getMeasurementsData function to obtain these measurements programmatically. The isNewDataReady function returns true when there is new spectrum data. Store the measured data in the variable data.

data = [];
for Iter = 1:1000
    Sinewave1 = Sineobject1();
    Sinewave2 = Sineobject2();
    Input = Sinewave1 + Sinewave2;
    NoisyInput = Input + 0.001*randn(1024,1);
    SA(NoisyInput);
     if SA.isNewDataReady
        data = [data;getMeasurementsData(SA)];
     end
end

The panes at the bottom of the scope window display the measurements that you have enabled. The values in these panes match the values in the last time step of the data variable. You can access the individual fields of data to obtain the various measurements programmatically.

Compare Peak Values

Use the PeakFinder property to obtain peak values. Verify that the peak values in the last time step of data match the values in the spectrum analyzer plot.

peakvalues = data.PeakFinder(end).Value 

peakvalues = 3×1

   26.3957
   22.7830
  -57.9977

frequencieskHz = data.PeakFinder(end).Frequency/1000

frequencieskHz = 3×1

    4.9957
    0.9905
   20.6719

More About

Convert the Power Between Units

Conversion of power between units on the Spectrum Analyzer window.

The Spectrum Analyzer provides three units to specify the power spectral density: Watts/Hz, dBm/Hz, and dBW/Hz. Corresponding units of power are Watts, dBm, and dBW. For electrical engineering applications, you can also view the RMS of your signal in Vrms or dBV. The default spectrum type is Power in dBm.

Convert the Power in Watts to dBW and dBm

Power in dBW is given by:

$$P_{\text{dBW}}=10{\log }_{10}(\text{power}\text{in}\text{watt}/1\text{watt})$$

Power in dBm is given by:

$$P_{\text{dBm}}=10{\log }_{10}(\text{power}\text{in}\text{watt}/1\text{milliwatt})$$

For a sine wave signal with an amplitude of 1 V, the power of a one-sided spectrum in Watts is given by:

$$\begin{array}{l}{P}_{\text{Watts}}=A^2/2\\ P_{\text{Watts}}=1/2\end{array}$$

Corresponding power in dBm is given by this equation.

$$\begin{array}{l}{P}_{\text{dBm}}=10{\log }_{10}(\text{power}\text{in}\text{watt}/1\text{milliwatt})\\ P_{\text{dBm}}=10{\log }_{10}(0.5/{10}^{-3})\\ P_{\text{dBm}}=26.9897\text{dBm}\end{array}$$

For a white noise signal, the spectrum is flat for all frequencies. Consider a white noise signal with a variance of 1e-4. The power per unit bandwidth therefore (P_{unitbandwidth}) is 1e-4. For a one-sided spectrum in the range [0 Fs/2], the total power of white noise in Watts is given by this equation.

$$\begin{array}{l}{P}_{\text{whitenoise}}=P_{\text{unitbandwidth}}.\text{number}\text{of}\text{frequency}\text{bins},\\ P_{\text{whitenoise}}=({10}^{-4}).\left(\frac{Fs/2}{RBW}\right)\end{array}$$

Fs is the input sample rate. The number of frequency bins is the ratio of total bandwidth to RBW. For a one-sided spectrum, the total bandwidth is half the sample rate. Consider a sample rate of 44100 Hz and a RBW of 21.53 Hz. With these values, the total power of white noise in Watts is 0.1024 W.

$$\begin{array}{l}{P}_{\text{whitenoise}}=10{\log }_{10}\left(0.1024/{10}^{-3}\right)\\ P_{\text{whitenoise}}=20.103\text{dBm}\end{array}$$

In dBm, the power of white noise can be calculated using 10*log10(0.1024/10^-3), which equals 20.103 dBm.

Convert Power in Watts to dBFS

If you set the spectral units to dBFS and set the full scale (FullScaleSource) to "auto", power in dBFS is computed as:

$$P_{\text{dBFS}}=20\cdot {\log }_{10}\left(\sqrt{P_{\text{watts}}}/\text{Full\_Scale}\right)$$

where:

• Pwatts is the power in watts

• For double and float signals, Full_Scale is the maximum value of the input signal.

• For fixed point or integer signals, Full_Scale is the maximum value that can be represented.

If you specify a manual full scale (set FullScaleSource to "property"), power in dBFS is given by:

$$P_{\text{FS}}=20\cdot {\log }_{10}\left(\sqrt{P_{\text{watts}}}/\text{FS}\right)$$

Where FS is the full-scaling factor specified in the FullScale property.

For a sine wave signal with an amplitude of 1 V, the power of a one-sided spectrum in Watts is given by:

$$\begin{array}{l}{P}_{\text{Watts}}=A^2/2\\ P_{\text{Watts}}=1/2\end{array}$$

The corresponding power in dBFS is given by:

$$\begin{array}{l}{P}_{\text{FS}}=20\cdot {\log }_{10}\left(\sqrt{1/2}/1\right)\\ P_{\text{FS}}=-3.0103\text{dBFS}\end{array}$$

To confirm the power value in the spectrum analyzer, run these commands:

Fs = 1000;  % Sampling frequency
sinef = dsp.SineWave(SampleRate=Fs,SamplesPerFrame=100);
scope = spectrumAnalyzer(SampleRate=Fs,...
   SpectrumUnits="dBFS",PlotAsTwoSidedSpectrum=false)

for ii = 1:100000
xsine = sinef();
scope(xsine)
end

Enable Peak Finder in the Measurements tab of the spectrum analyzer toolstrip.

Convert the Power in dBm to RMS in Vrms

Power in dBm is given by:

$$P_{\text{dBm}}=10{\log }_{10}(\text{power}\text{in}\text{watt}/1\text{milliwatt})$$

Voltage in RMS is given by:

$$V_{\text{rms}}={10}^{P_{\text{dBm}}/20}\sqrt{{10}^{-3}}$$

From the previous example, P_dBm equals 26.9897 dBm. The V_rms is calculated as

$$V_{\text{rms}}={10}^{26.9897/20}\sqrt{0.001}$$

which equals 0.7071.

To confirm this value using the peak finder:

1. In the Analyzer Tab of the Spectrum Analyzer toolstrip, select Spectrum > RMS.

2. Enable Peak Finder in the Measurements tab.

Cursor Measurements

Measure signal values using vertical waveform cursors that track along the signal.

When you click the Data Cursors button in the Measurements tab of the Spectrum Analyzer, the spectrum display shows vertical cursors on each signal. Each cursor tracks a vertical line along the signal. The scope displays the difference between x- and y-values of the signal at the two cursors in the box between the cursors.

To enable cursor measurements, click the Data Cursors button in the Measurements tab. The cursors appear only when the Spectrum Analyzer has at least one signal in its display.

You can use the mouse to move the vertical cursors left and right.

In the Measurements tab, click the Data Cursors drop-down arrow to select one of these options:

• Snap to Data — To position the cursors on the signal data points.

• Lock Cursor Spacing — To lock the frequency difference between the two cursors.

For modifying the cursor measurements programmatically, see the CursorMeasurementsConfiguration object.

Peak Finder Measurements

Compute and display peak values in the scope display.

When you click on the Peak Finder button in the Measurements tab of the Spectrum Analyzer, an arrow appears on the plot at each maxima and a Peaks panel appears at the bottom of the scope window. The Spectrum Analyzer computes peaks from the portion of the input signal that is currently on display in the scope, and the Peaks panel shows the peak values and the frequencies at which they occur.

The Peaks section in the Measurements tab allows you to specify the number of peaks you want the scope to display, the minimum height above which you want the scope to detect peaks, the minimum distance between peaks, and label the peaks.

The Spectrum Analyzer algorithm defines a peak as a local maximum with lower values present on either side of the peak. It does not consider end points as peaks. For more information on the algorithm, see the findpeaks function.

The peaks are valid for any units of the input signal. The letter after the value associated with each measurement indicates the abbreviation for the appropriate International System of Units (SI) prefix, such as m for milli-. For example, if the input signal is measured in volts, an m next to a measurement value indicates that this value is in units of millivolts.

For modifying the peak finder measurements programmatically, see the PeakFinderConfiguration object. For more information on these settings in the UI, see Peaks.

Distortion Measurements

Measure harmonic distortion and intermodulation distortion.

When you click the Distortion button in the Distortion section of the Measurements tab, a distortion panel opens at the bottom of the Spectrum Analyzer window. This panel shows the harmonic and distortion measurement values for the input signal currently on display in the scope. The Distortion section in the Measurements tab allows you to specify the distortion type, number of harmonics, and even label the harmonics.

Note

For an accurate measurement, ensure that the fundamental signal (for harmonics) or primary tones (for intermodulation) is larger than any spurious or harmonic content. To do so, you may need to adjust the resolution bandwidth (RBW) of the Spectrum Analyzer. Make sure that the bandwidth is low enough to isolate the signal and harmonics from spurious noise content. In general, you should set the RBW value such that there is at least a 10 dB separation between the peaks of the sinusoids and the noise floor. You also might need to select a different spectral window to obtain a valid measurement.

You can set the Distortion Type parameter to one of these values:

• Harmonic –– Select Harmonic if your input is a single sinusoid.

• Intermodulation –– Select Intermodulation if your input is two equal-amplitude sinusoids. Intermodulation can help you determine distortion when the scope uses only a small portion of the available bandwidth.

See Distortion Measurements for information on how distortion measurements are calculated.

Harmonic Distortion

When you set the Distortion Type to Harmonic, these fields appear in the Harmonic Distortion panel at the bottom of the Spectrum Analyzer window.

• H1 — Fundamental frequency in Hz and its power in decibels of the measured power referenced to 1 milliwatt (dBm).

• H2, H3, ... — Harmonics frequencies in Hz and their power in decibels relative to the carrier (dBc). If the harmonics are at the same level or exceed the fundamental frequency, reduce the input power.

• THD — Total harmonic distortion. This value represents the ratio of the power in the harmonics D to the power in the fundamental frequency S. If the noise power is too high in relation to the harmonics, the THD value is not accurate. In this case, lower the resolution bandwidth or select a different spectral window.

  $$THD=10\cdot {\log }_{10}(D/S)$$

• SNR — Signal-to-noise ratio (SNR). This value represents the ratio of the power in the fundamental frequency S to the power of all nonharmonic content N, including spurious signals, in decibels relative to the carrier (dBc).

  $$SNR=10\cdot {\log }_{10}(S/N)$$

  If you see –– as the reported SNR, the total nonharmonic content of your signal is less than 30% of the total signal.

• SINAD — Signal-to-noise-and-distortion ratio. This value represents the ratio of the power in the fundamental frequency S to all other content (including noise N and harmonic distortion D) in decibels relative to the carrier (dBc).

  $$SINAD=10\cdot {\log }_{10}\left(\frac{S}{N+D}\right)$$

• SFDR — Spurious-free dynamic range (SFDR). This value represents the ratio of the power in the fundamental frequency S to power of the largest spurious signal R regardless of where it falls in the frequency spectrum. The worst spurious signal might or might not be a harmonic of the original signal. SFDR represents the smallest value of a signal that can be distinguished from a large interfering signal. SFDR includes harmonics.

  $$SNR=10\cdot {\log }_{10}(S/R)$$

The harmonic distortion measurement automatically locates the largest sinusoidal component (fundamental signal frequency). It then computes the harmonic frequencies and power in each harmonic in your signal and ignores any DC component. The measurement does not include any harmonics that are outside the Spectrum Analyzer frequency span. Adjust your frequency span so that it includes all the desired harmonics.

Note

To view the best harmonics, make sure that your fundamental frequency is set high enough to resolve the harmonics. However, this frequency should not be so high that aliasing occurs. For the best display of harmonic distortion, your plot should not show skirts, which indicate frequency leakage. The noise floor should be visible.

For a better display, try a Kaiser window with a large sidelobe attenuation (e.g. between 100–300 db).

Intermodulation Distortion

When you set the Distortion Type to Intermodulation, the following fields appear in the Intermodulation Distortion panel at the bottom of the Spectrum Analyzer window.

• F1 — Lower fundamental first-order frequency.

• F2 — Upper fundamental first-order frequency.

• 2F1 - F2 — Lower intermodulation product from third-order harmonics.

• 2F2 - F1 — Upper intermodulation product from third-order harmonics.

• TOI — Third-order intercept point. If the noise power is too high in relation to the harmonics, the TOI value will not be accurate. In this case, you should lower the resolution bandwidth or select a different spectral window. If the TOI has the same amplitude as the input two-tone signal, reduce the power of that input signal.

The intermodulation distortion measurement automatically locates the fundamental and the first-order frequencies (F1 and F2). It then computes the frequencies of the third-order intermodulation products (2F1−F2 and 2F2−F1).

For modifying the distortion measurements programmatically, see the DistortionMeasurementsConfiguration object. For more information on these settings in the UI, see Distortion.

Channel Measurements

Measure the occupied bandwidth or adjacent channel power ratio (ACPR).

When you click the Channel Measurements button in the Channel Measurements tab, a channel measurements panel opens at the bottom of the Spectrum Analyzer window. This panel displays the occupied bandwidth or the adjacent channel power ratio measurements. In the Channel Measurements tab, you can specify the occupied bandwidth or the ACPR settings, frequency span, center frequency, and start and stop frequencies.

You can select the channel measurements Type to:

• Occupied BW –– Occupied bandwidth

• ACPR –– Ratio of the power of the main channel to the power of the adjacent channel

For more details on how the Spectrum Analyzer calculates the occupied bandwidth, see Occupied BW.

Occupied Bandwidth

When you set the Type of channel measurement to compute and display to Occupied BW, these fields appear in the measurements panel at the bottom of the scope window.

• Channel Power — Total power in the channel

• Occupied BW — Bandwidth containing the specified Occupied BW (%) of the total power of the spectrum.

• Frequency Error — Difference between the center of the occupied band and the center frequency (Center Frequency (Hz)) of the channel

ACPR

When you set the Type of channel measurement to compute and display to ACPR, these fields appear in the measurements panel at the bottom of the scope window.

• Lower (Rel Power (dBc)) — Ratio of the power of the lower sideband to the power of the main channel

• Upper (Rel Power (dBc)) — Ratio of the power of the upper sideband to the power of the main channel

To modify the channel measurements programmatically, see the ChannelMeasurementsConfiguration object. For more information on these settings in the UI, see Channel Measurements.

Spectral Mask

Visualize spectrum limits and compare spectrum values to specification values.

Add upper and lower masks to the Spectrum Analyzer to visualize spectrum limits and compare spectrum values to specification values. To enable the Spectral Mask tab, select Spectrum in the Analyzer tab. When you click the Upper Mask and Lower Mask buttons in the Spectral Mask tab, a Spectral Mask panel opens at the bottom of the Spectrum Analyzer window. This panel provides information on pass-fail statistics of masks, names of masks currently failing or passing, and names of channels causing the failure.

You can modify the mask settings in the Spectral Mask tab. For more information on these settings in the UI, see Spectral Mask. For modifying the channel measurements programmatically, see the SpectralMaskConfiguration object.

Check Spectral Masks

You can check the status of the spectral mask using the getSpectralMaskStatus function. This function gives details on the number of times a mask succeeded or failed, names of channels causing mask failure, and so on.

You can even use the MaskTestFailed event to perform an action every time the mask fails. To trigger a function when the mask fails, create a listener to the MaskTestFailed event and define a callback function to trigger it. For more details about using events, see Events.

Customize Visualization

Set configuration and style settings in the Spectrum Analyzer.

To control the settings of the display and labels, color and styling, click on Settings () in the Analyzer tab of the Spectrum Analyzer toolstrip.

In the dialog box that opens, you can customize the font size, plot type, y-axis properties of the spectrum plot, and color map properties of the spectrogram plot. You can change the color of the spectrum plot, background, axes, and labels and also change the line properties.

When you view the spectrum or the spectrogram, you see only the relevant options. For more details about these options, see Configuration > Spectrum Settings.

Display Controls

Zoom and pan axes using display controls.

To scale the plot axes, use the mouse to pan around the axes and the scroll button on your mouse to zoom in and out of the plot. Additionally, you can use the buttons that appear when you hover over the plot window.

• — Maximize the axes, hide all labels and inset the axes values.

• — Zoom in on the plot.

• — Pan the plot.

• — Autoscale the axes to fit the shown data.

Tips

• To close the scope window and clear its associated data, use the MATLAB clear function.

• To hide or show the scope window, use the hide and show functions.

• Use the MATLAB mcc function to compile code containing a Spectrum Analyzer.

Algorithms

Spectrum Estimation — Filter Bank

When you choose the Filter Bank method, the Spectrum Analyzer uses an analysis filter bank to estimate the power spectrum.

The filter bank splits the broadband input signal x(n), of sample rate fs, into multiple narrow band signals y₀(m), y₁(m), … , y_M-1(m), of sample rate fs/M.

The variable M represents the number of frequency bands in the filter bank. In the Spectrum Analyzer, M is equal to the number of data points needed to achieve the specified RBW value or 1024, whichever is larger. For more information on the analysis filter bank and its implementation, see the More About and the Algorithm sections in the dsp.Channelizer object.

After the Spectrum Analyzer splits the broadband input signal into multiple narrow bands, it computes the power in each narrow frequency band using the following equation. Each Z_i value is the power estimate over that narrow frequency band.

$$Z_i=\frac{1}{L}{\displaystyle \sum _{m=0}^{L-1}{\left|y_i[m]\right|}^2}$$

L is length of the narrowband signal y_i(m) and i = 1, 2, …, M−1.

The power values in all the narrow frequency bands (denoted by Z_i) form the Z vector.

$$Z=[Z_0,Z_1,Z_2,\cdots ,Z_{M-1}]$$

The Spectrum Analyzer averages the current Z vector with the previous Z vectors using one of the two moving average methods: video bandwidth or exponential weighting. The output of the averaging operation forms the spectral estimate vector. For details on the two averaging methods, see Averaging Method.

The Spectrum Analyzer uses the value you specify in the RBW (Hz) parameter to determine the input frame length. To view the RBW (Hz) parameter in the scope, click the Analyzer tab on the Spectrum Analyzer toolstrip and navigate to the Bandwidth section.

Spectrum Analyzer requires a minimum number of samples to compute a spectral estimate. This value is directly related to the resolution bandwidth property RBW (Hz).

When you set RBW (Hz) to:

• Auto –– The Spectrum Analyzer requires 1024 samples to update the display. The Spectrum Analyzer determines the appropriate resolution bandwidth to ensure that there are 1024 RBW intervals over the specified frequency span. When you set RBW (Hz) to Auto, the Spectrum Analyzer calculates RBW using this equation.

  $$RB{W}_{auto}=\frac{span}{1024}$$

• scalar value –– The Spectrum Analyzer calculates the number of samples N_samples using this equation.

  $$N_{samples}=\frac{F_s}{RBW}$$

  F_s is the sample rate of the input signal as specified in the Sample Rate (Hz) property. To view the Sample Rate (Hz) in the scope, click the Analyzer tab on the Spectrum Analyzer toolstrip and navigate to the Bandwidth section.

  When you specify a resolution bandwidth using the RBW (Hz) parameter, you must specify a value such that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW must be greater than two.

  $$\frac{span}{RBW}>2$$

span is the frequency span over which the Spectrum Analyzer computes and plots the spectrum. To view the Span (Hz) in the scope, click the Estimation tab on the Spectrum Analyzer toolstrip and navigate to the Frequency Options section. To enable this property, set Frequency Span to Span and Center Frequency.

When the number of input samples is not sufficient to achieve the specified resolution bandwidth, the Spectrum Analyzer displays a message similar to this one.

The Spectrum Analyzer removes this message and displays a spectral estimate once you provide enough input samples.

Spectrum Estimation — Welch's Method

When you select the Welch method, the power spectrum estimate is the averaged modified periodograms.

The algorithm in the Spectrum Analyzer consists of these steps:

1. The block buffers the input into N-point data segments. Each data segment is split into P overlapping data segments, each of length M, overlapping by D points. The data segments can be represented as:

   $$\begin{array}{l}{x}_i(n)=x(n+iD),n=0,1,\mathrm{...},M-1\\ i=0,1,\mathrm{...},P-1\end{array}$$

   • If D = M/2, the overlap is 50%.

   • If D = 0, the overlap is 0%.

2. Apply a window to each of the P overlapping data segments in the time domain.

   The Spectrum Analyzer uses RBW (Hz) in the Analyzer tab to determine the data window length N_window internally. Then, it partitions the input signal into a number of windowed data segments.

   Most window functions afford more influence to the data at the center of the set than to the data at the edges, which represents a loss of information. To mitigate that loss, the individual data sets are commonly overlapped in time. For each windowed segment, compute the periodogram by computing the discrete Fourier transform. Then compute the squared magnitude of the result and divide the result by M.

   $$P_{xx}^i(f)=\frac{1}{MU}{\left|{\displaystyle \sum _{n=0}^{M-1}{x}_i(n)w(n)e^{-j2\pi fn}}\right|}^2,i=0,1,\mathrm{...},P-1$$

   where U is the normalization factor for the power in the window function and is given by

   $$U=\frac{1}{M}{\displaystyle \sum _{n=0}^{M-1}{w}^2(n)}$$

   You can specify the window using the Window parameter in the Estimation tab of the Spectrum Analyzer toolstrip.

3. The Spectrum Analyzer calculates and plots the power spectrum, power spectrum density, and RMS using the modified Periodogram estimator. For more information about the Periodogram method, see periodogram.

   To determine the power spectrum estimate for Welch's method, the Spectrum Analyzer averages the result of the periodograms for the last P data segments. The averaging reduces the variance, compared to the original N-point data segment. For more details on the averaging, see Averaging Method.

   $$\mathrm{PSD}\left(f\right)=\frac{1}{P}{\displaystyle \sum _{i=0}^{P-1}{P}_{xx}^i(f)}$$

4. The Spectrum Analyzer computes the power spectral density using:

   $$\mathrm{PSD}\left(f\right)=\frac{1}{P*F_s}{\displaystyle \sum _{i=0}^{P-1}{P}_{xx}^i(f)}$$

5. The power spectrum is the product of the power spectral density and the resolution bandwidth, as given by this equation.

   $$P_{spectrum}\left(f\right)=\mathrm{PSD}\left(f\right)\times RBW=\mathrm{PSD}\left(f\right)\times \frac{F_s\times NENBW}{N_{window}}$$

6. The Spectrum Analyzer plots the power as a spectrogram in the Spectrogram mode. Each line of the spectrogram is one periodogram. The time resolution of each line is 1/RBW, which is the minimum attainable resolution. Achieving the resolution you want might require combining several periodograms. You then use interpolation to calculate noninteger values of 1/RBW. In the spectrogram display, time scrolls from top to bottom, so the most recent data appears at the top of the display. The offset shows the time value at which the center of the most current spectrogram line occurred.

The Spectrum Analyzer requires a minimum number of samples to compute a spectral estimate. This value is directly related to the resolution bandwidth (RBW).

$$N_{samples}=\frac{\left(1-\frac{O_p}{100}\right)\times NENBW\times F_s}{RBW}$$

where O_p is the overlap percentage, NENBW is the normalized effective noise bandwidth, F_s is the input sample rate, and RBW is the resolution bandwidth.

The Spectrum Analyzer shows the number of samples per update in the Spectrum Analyzer status bar.

You can enable Samples/Update in the status bar only when you set Input Domain to Time and Method to Welch in the Estimation tab on the Spectrum Analyzer toolstrip.

Overlap Percentage (O_p)

The overlap percentage O_p is the value you specify in the Overlap % property. To view the Overlap % in the scope, click the Estimation tab on the Spectrum Analyzer toolstrip and navigate to the Window Options section.

When you increase the overlap percentage, the Spectrum Analyzer needs fewer new input samples to compute a new spectral update.

Op	Nsamples
0%	100
50%	50
80%	20

Normalized Effective Noise Bandwidth (NENBW)

The normalized effective noise bandwidth NENBW is a window parameter that measures the noise performance of the window. NENBW is determined using the window length and the window coefficients, and is given by the following equation:

$$NENBW=N_{window}\times \frac{{\displaystyle \sum _{n=1}^{N_{window}}{w}^2(n)}}{{\left[{\displaystyle \sum _{n=1}^{N_{window}}w(n)}\right]}^2}$$

w(n) denotes the vector of window coefficients (calculated internally). N_window is the window length the Spectrum Analyzer needs to compute one spectral update, and is directly related to the resolution bandwidth and normalized effective noise bandwidth.

$$N_{window}=\frac{NENBW\times F_s}{RBW}$$

The rectangular window has the smallest NENBW, with a value of 1. All other windows have a larger NENBW value. For example, the Hann window has an NENBW value of approximately 1.5.

The Spectrum Analyzer shows the value of NENBW in the Spectrum Analyzer status bar.

You can enable NENBW only when you set Input Domain to Time and Method to Welch in the Estimation tab on the Spectrum Analyzer toolstrip.

Input Sample Rate (Fs)

F_s is the sample rate of the input signal. To view the Sample Rate (Hz) in the scope, click the Analyzer tab on the Spectrum Analyzer toolstrip and navigate to the Bandwidth section. You can enable this property in the status bar at the bottom of the Spectrum Analyzer window. Right-click the status bar and select Sample Rate.

Resolution Bandwidth (RBW)

Resolution bandwidth controls the spectral resolution of the displayed signal. The RBW value determines the spacing between frequencies that the scope can resolve. A smaller value gives a higher spectral resolution and lowers the noise floor, that is, the Spectrum Analyzer can resolve frequencies that are closer to each other. However, this comes at the cost of a longer sweep time.

You can set the resolution bandwidth through the RBW (Hz) property. To view RBW (Hz) in the scope, click the Analyzer tab on the Spectrum Analyzer toolstrip and navigate to the Bandwidth section.

When you set RBW (Hz) to:

• Auto –– The Spectrum Analyzer requires 1024 samples to update the display. The Spectrum Analyzer determines the appropriate resolution bandwidth to ensure that there are 1024 RBW intervals over the specified frequency span. When you set RBW (Hz) to Auto, the Spectrum Analyzer calculates using this equation.

  $$RB{W}_{auto}=\frac{span}{1024}$$

• scalar value –– Specify a value such that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW must be greater than two:

  $$\frac{span}{RBW}>2$$

span is the frequency span over which the Spectrum Analyzer computes and plots the spectrum. Spectrum Analyzer shows the span through the Span (Hz) property. To view the Span (Hz) in the scope, click the Estimation tab on the Spectrum Analyzer toolstrip, navigate to the Frequency Options section, and set Frequency Span to Span and Center Frequency.

When the number of input samples is not sufficient to achieve the specified resolution bandwidth, the Spectrum Analyzer displays a message similar to this one.

The Spectrum Analyzer removes this message and displays a spectral estimate once you provide enough input samples.

You can enable this property in the status bar at the bottom of the Spectrum Analyzer window. Right-click the status bar and select RBW.

Nyquist Frequency Interval

When you plot the two-sided spectrum by selecting Two-Sided Spectrum in the Spectrum or Spectrogram tab, the Nyquist frequency interval is $$\left[-\frac{SampleRate}{2},\frac{SampleRate}{2}\right]+FrequencyOffset$$ Hz.

When you clear the Two-Sided Spectrum, the Nyquist frequency interval is $$\left[0,\frac{SampleRate}{2}\right]+FrequencyOffset$$ Hz.

Frequency Vector

When you set Frequency (Hz) to Auto, the software calculates the frequency vector for the frequency-domain input.

When you plot the two-sided spectrum by selecting Two-Sided Spectrum in the Spectrum or Spectrogram tab, the frequency vector is:

$$\left[-\frac{SampleRate}{2},\frac{SampleRate}{2}\right]$$

When you clear the Two-Sided Spectrum, the frequency vector is:

$$\left[0,\frac{SampleRate}{2}\right]$$

Occupied BW

The Spectrum Analyzer calculates Occupied BW using these steps.

1. Calculate the total power in the measured frequency range.

2. Determine the lower frequency value. Starting at the lowest frequency in the range and moving upward, sum the power distributed in each frequency until the result is

   $$\frac{100-OccupiedBW\%}{2}$$

   of the total power.

3. Determine the upper frequency value. Starting at the highest frequency in the range and moving downward, sum the power distributed in each frequency until the result reaches

   $$\frac{100-OccupiedBW\%}{2}$$

   of the total power.

4. The bandwidth between the lower and upper power frequency values is the occupied bandwidth.

5. The frequency halfway between the lower and upper frequency values is the center frequency.

Distortion Measurements

The Spectrum Analyzer calculates Distortion Measurements using these steps.

1. Estimate spectral content by finding peaks in the spectrum. When the algorithm detects a peak, it records the width of the peak and clears all monotonically decreasing values by treating all these values as if they belong to the peak. Using this method, the algorithm removes all spectral content centered at DC (0 Hz) from the spectrum and records the amount of bandwidth cleared (W₀).

2. Determine the fundamental power (P₁) from the remaining maximum value of the displayed spectrum. Create a local estimate (Fe₁) of the fundamental frequency by computing the central moment of the power near the peak. Record the bandwidth of the fundamental power content (W₁). Then remove the power from the fundamental as in step 1.

3. Determine the power and width of the higher-order harmonics (P₂, W₂, P₃, W₃, etc.) in succession by examining the frequencies closest to the appropriate multiple of the local estimate (Fe₁). Remove any spectral content that decreases monotonically about the harmonic frequency from the spectrum before proceeding to the next harmonic.

4. After removing the DC, fundamental, and harmonic content from the spectrum, examine the power of the remaining spectrum for its sum (P_remaining), peak value (P_maxspur), and median value (P_estnoise).

5. Compute the sum of all the removed bandwidth as W_sum = W₀ + W₁ + W₂ +...+ W_n.

   Compute the sum of powers of the second and higher-order harmonics as P_harmonic = P₂ + P₃ + P₄ +...+ P_n.

6. Estimate the sum of the noise power as:

   $$P_{noise}=(P_{remaining}\cdot dF+P_{est.noise}\cdot W_{sum})/RBW$$

   Where dF is the absolute difference between frequency bins, and RBW is the resolution bandwidth of the window.

7. Then compute the metrics for SNR, THD, SINAD, and SFDR from the estimates.

   $$\begin{array}{l}THD=10\cdot {\log }_{10}\left(\frac{P_{harmonic}}{P_1}\right)\\ SINAD=10\cdot {\log }_{10}\left(\frac{P_1}{P_{harmonic}+P_{noise}}\right)\\ SNR=10\cdot {\log }_{10}\left(\frac{P_1}{P_{noise}}\right)\\ SFDR=10\cdot {\log }_{10}\left(\frac{P_1}{\max \left(P_{maxspur},\max \left(P_2,P_3,\mathrm{...},P_n\right)\right)}\right)\end{array}$$

Harmonic Measurements

1. The harmonic distortion measurements use the spectrum trace shown in the display as the input to the measurements. The default Hann window setting of the Spectrum Analyzer might exhibit leakage that can completely mask the noise floor of the measured signal.

   The harmonic measurements attempt to correct for leakage by ignoring all frequency content that decreases monotonically away from the maximum of harmonic peaks. If the window leakage covers more than 70% of the frequency bandwidth in your spectrum, you may see a blank reading (–) reported for SNR and SINAD. If your application can tolerate the increased equivalent noise bandwidth (ENBW), consider using a Kaiser window with a high attenuation (up to 330 dB) to minimize spectral leakage.

2. Ignore the DC component.

3. After windowing, the width of each harmonic component masks the noise power in the neighborhood of the fundamental frequency and harmonics. To estimate the noise power in each region, the Spectrum Analyzer computes the median noise level in the nonharmonic areas of the spectrum. It then extrapolates that value into each region.

4. N^th order intermodulation products occur at A*F1 + B*F2,

   where F1 and F2 are the sinusoid input frequencies and |A| + |B| = N. A and B are integer values.

5. For intermodulation measurements, compute the third-order intercept (TOI) point as follows.

   • TOI_lower = P_F1 + (P_F2 - P_(2F1-F2))/2

   • TOI_upper = P_F2 + (P_F1 - P_(2F2-F1))/2

   • TOI = + (TOI_lower + TOI_upper)/2

   Where P is power in decibels of the measured power referenced to 1 milliwatt (dBm).

Averaging Method

The Spectrum Analyzer can calculate the moving average using two methods:

• Video bandwidth — The Spectrum Analyzer uses a time-domain lowpass filter to smooth the noise in the signal. The video bandwidth (VBW) filter smoothes the trace and decreases noise, and the Spectrum Analyzer applies the filter to the data before displaying it.

  Video bandwidth is the bandwidth of the lowpass filter that Spectrum Analyzer uses to average or smooth the noise in the signal before displaying it in the scope. The Spectrum Analyzer computes the video bandwidth using this equation:

  $$VBW=\frac{(1-\lambda )RBW}{2\pi \lambda NENBW}$$

  where,

  • λ is the forgetting factor.

  • RBW is the resolution bandwidth.

  • NENBW is the normalized effective noise bandwidth.

  Video bandwidth does not affect the level of the noise (noise floor), but only increases the signal-to-noise ratio and smoothes the trace of the noise. When you decrease the value of VBW, the signal-to-noise ratio improves.

  The cutoff frequency of the video bandwidth filter is given by:

  $${\omega }_c=\frac{2\pi VBW}{F_s/NFFT}$$

  where Fs is the input sample rate and NFFT is the number of FFT points.

  The Spectrum Analyzer shows the values of sample rate, VBW, and NFFT in the status bar at the bottom of the display. To enable, right-click the status bar and select Sample Rate, VBW, and NFFT.

• Exponential — The moving average algorithm uses the exponential weighting method to update the weights and compute the moving average recursively for each Z vector that comes in by using the following recursive equations:

  $$\begin{array}{l}{w}_N=\lambda w_{N-1}+1\\ {\overline{z}}_N=\left(1-\frac{1}{w_N}\right){\overline{z}}_{N-1}+\left(\frac{1}{w_N}\right)z_N\end{array}$$

  • λ — Forgetting factor

  • $$w_N$$ — Weighting factor applied to the current Z vector

  • $$z_N$$ — Current Z vector

  • $${\overline{z}}_{N-1}$$ — Moving average until the previous Z vector

  • $$\left(1-\frac{1}{w_N}\right){\overline{z}}_{N-1}$$ — Effect of the previous Z vectors on the average

  • $${\overline{z}}_N$$ — Moving average including the current Z vector

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• The spectrumAnalyzer object supports MEX code generation by treating the calls to the object as extrinsic.

• The object does not support code generation for standalone applications.

Version History

Introduced in R2022a

R2023a: SampleRate and PlotAsTwoSidedSpectrum properties are tunable

Starting in R2023a, the SampleRate and PlotAsTwoSidedSpectrum properties are tunable, so you can change the values of these properties even when the object is locked.

R2022b: Channel names support array of strings

Starting in R2022b, you can specify the ChannelNames property of the spectrumAnalyzer object as an array of strings.

sa = spectrumAnalyzer(ChannelNames=["Input", "Output"]);

R2022b: New FilterSharpness property

When the object uses the filter bank spectral estimation method, you can now increase the sharpness of the filter bank in the spectrumAnalyzer object . Increasing the filter sharpness decreases the spectral leakage and gives a more accurate power reading.

R2022b: New fields on Spectrum Analyzer status bar

Starting in R2022b, the Spectrum Analyzer displays these fields on the status bar:

• Updates –– This field shows when you select Spectrum updates processed in the Customize Status Bar window.

• Channel number –– This field shows when you select Spectrogram channel in the Customize Status Bar window.

  The Spectrogram channel field is enabled only when the display shows spectrogram.

To enable these fields, right-click the status bar and select the properties in the Customize Status Bar window.

For more details, see Configure Spectrum Analyzer.

R2022b: Support for waveform cursors in spectrogram mode

Starting in R2022b, the Spectrum Analyzer supports data cursors even when the scope shows only the spectrogram display.

In the command line, you can edit the CursorMeasurementsConfiguration object when you set the ViewType to "spectrogram".

R2022b: Enhancements to Data Cursor Measurements

Starting in R2022b, the CursorMeasurementsConfiguration object has the new LockSpacing property. Using this property, you can lock the spacing between waveform cursors in the scope window.

In the Measurements tab of the scope UI window, these data cursor settings are new:

• Lock cursor spacing –– This setting corresponds to the LockSpacing property in the CursorMesaurementsConfiguration object.

• X location –– These fields are enabled and correspond to the XLocation property in the CursorMesaurementsConfiguration object.