how to do beam steering in elevation plane in edit ScanRadarExample??

%% Scan Radar Using a Uniform Rectangular Array % This example simulates a phased array radar that periodically scans a % predefined surveillance region. A 900-element rectangular array is used % in this monostatic radar. Steps are introduced to derive the radar % parameters according to specifications. After synthesizing the received % pulses, detection and range estimation are performed. Finally, Doppler % estimation is used to obtain the speed of each target.

% Copyright 2010-2016 The MathWorks, Inc.

%% Radar Definition % First we create a phased array radar. We reuse most of the subsystems % built in the example Designing a Basic % Monostatic Pulse Radar. Readers are encouraged to explore the details of % radar system % design through that example. A major difference is that we use a % 30-by-30 uniform rectangular array (URA) in place of the original single % antenna.

%% % The existing radar design meets the following specifications. pd = 0.9; % Probability of detection pfa = 1e-6; % Probability of false alarm max_range = 5000; % Maximum unambiguous range tgt_rcs = 1; % Required target radar cross section int_pulsenum = 10; % Number of pulses to integrate

%% % Load the radar system and retrieve system parameters.

load BasicMonostaticRadarExampleData;

fc = radiator.OperatingFrequency; % Operating frequency (Hz) v = radiator.PropagationSpeed; % Wave propagation speed (m/s) lambda = v/fc; % Wavelength (m) fs = waveform.SampleRate; % Sampling frequency (Hz) prf = waveform.PRF; % Pulse repetition frequency (Hz)

%% % Next, we define a 30-by-30 uniform rectangular array.

ura = phased.URA('Element',antenna,... 'Size',[30 30],'ElementSpacing',[lambda/2, lambda/2]); % Configure the antenna elements such that they only transmit forward ura.Element.BackBaffled = true;

% Visualize the response pattern. pattern(ura,fc,'PropagationSpeed',physconst('LightSpeed'),... 'Type','powerdb');

%% % Associate the array with the radiator and collector.

radiator.Sensor = ura; collector.Sensor = ura;

% We need to set the WeightsInputPort property to true to enable it to % accept transmit beamforming weights radiator.WeightsInputPort = true;

%% % Now we need to recalculate the transmit power. The original transmit % power was calculated based on a single antenna. For a 900-element array, % the power required for each element is much less.

% Calculate the array gain arraygain = phased.ArrayGain('SensorArray',ura,'PropagationSpeed',v); ag = arraygain(fc,[0;0]);

% Use the radar equation to calculate the peak power snr_min = albersheim(pd, pfa, int_pulsenum); peak_power = radareqpow(lambda,max_range,snr_min,waveform.PulseWidth,... 'RCS',tgt_rcs,'Gain',transmitter.Gain + ag)

%% % The new peak power is 0.0065 Watts.

% Set the peak power of the transmitter transmitter.PeakPower = peak_power;

%% % We also need to design the scanning schedule of the phased array. To % simplify the example, we only search in the azimuth dimension. We require % the radar to search from 45 degrees to -45 degrees in azimuth. The % revisit time should be less than 1 second, meaning that the radar should % revisit the same azimuth angle within 1 second.

initialAz = 45; endAz = -45; volumnAz = initialAz - endAz;

%% % To determine the required number of scans, we need to know the beamwidth % of the array response. We use an empirical formula to estimate the 3-dB % beamwidth. % % $$G=\frac{4\pi}{\theta^2}$$ % % where $G$ is the array gain and $\theta$ is the 3-dB beamwidth.

% Calculate 3-dB beamwidth theta = radtodeg(sqrt(4*pi/db2pow(ag)))

%% % The 3-dB beamwidth is 6.77 degrees. To allow for some beam overlap in % space, we choose the scan step to be 6 degrees.

scanstep = -6; scangrid = initialAz+scanstep/2:scanstep:endAz; numscans = length(scangrid); pulsenum = int_pulsenum*numscans;

% Calculate revisit time revisitTime = pulsenum/prf

%% % The resulting revisit time is 0.005 second, well below the prescribed % upper limit of 1 second.

%% Target Definition % We want to simulate the pulse returns from two non-fluctuating targets, % both at 0 degrees elevation. The first target is approaching to the % radar, while the second target is moving away from the radar.

tgtpos = [[3532.63; 0; 800],[2020.66; 0; 0]]; tgtvel = [[1; 50; 0],[160; 80; 0]]; tgtmotion = phased.Platform('InitialPosition',tgtpos,'Velocity',tgtvel);

tgtrcs = [1.6 2.2]; target = phased.RadarTarget('MeanRCS',tgtrcs,'OperatingFrequency',fc);

% Calculate the range, angle, and speed of the targets [tgtrng,tgtang] = rangeangle(tgtmotion.InitialPosition,... sensormotion.InitialPosition);

numtargets = length(target.MeanRCS);

%% Pulse Synthesis % Now that all subsystems are defined, we can proceed to simulate the % received signals. The total simulation time corresponds to one pass % through the surveillance region. Because the reflected signals are % received by an array, we use a beamformer pointing to the steering % direction to obtain the combined signal.

% Create the steering vector for transmit beamforming steeringvec = phased.SteeringVector('SensorArray',ura,... 'PropagationSpeed',v);

% Create the receiving beamformer beamformer = phased.PhaseShiftBeamformer('SensorArray',ura,... 'OperatingFrequency',fc,'PropagationSpeed',v,... 'DirectionSource','Input port');

% Define propagation channel for each target channel = phased.FreeSpace(... 'SampleRate',fs,... 'TwoWayPropagation',true,... 'OperatingFrequency',fc);

fast_time_grid = unigrid(0, 1/fs, 1/prf, '[)');

% Pre-allocate array for improved processing speed rxpulses = zeros(numel(fast_time_grid),pulsenum);

for m = 1:pulsenum

    % Update sensor and target positions
    [sensorpos,sensorvel] = sensormotion(1/prf);
    [tgtpos,tgtvel] = tgtmotion(1/prf);

    % Calculate the target angles as seen by the sensor
    [tgtrng,tgtang] = rangeangle(tgtpos,sensorpos);

    % Calculate steering vector for current scan angle
    scanid = floor((m-1)/int_pulsenum) + 1;
    sv = steeringvec(fc,scangrid(scanid));
    w = conj(sv);

    % Form transmit beam for this scan angle and simulate propagation
    pulse = waveform();
    [txsig,txstatus] = transmitter(pulse);
    txsig = radiator(txsig,tgtang,w);
    txsig = channel(txsig,sensorpos,tgtpos,sensorvel,tgtvel);

    % Reflect pulse off of targets
    tgtsig = target(txsig);

    % Beamform the target returns received at the sensor
    rxsig = collector(tgtsig,tgtang);
    rxsig = receiver(rxsig,~(txstatus>0));    
    rxpulses(:,m) = beamformer(rxsig,[scangrid(scanid);0]);
end

%% Matched Filter % To process the received signal, we first pass it through a matched % filter, then integrate all pulses for each scan angle.

% Matched filtering matchingcoeff = getMatchedFilter(waveform); matchedfilter = phased.MatchedFilter(... 'Coefficients',matchingcoeff,... 'GainOutputPort',true); [mf_pulses, mfgain] = matchedfilter(rxpulses); mf_pulses = reshape(mf_pulses,[],int_pulsenum,numscans);

matchingdelay = size(matchingcoeff,1)-1; sz_mfpulses = size(mf_pulses); mf_pulses = [mf_pulses(matchingdelay+1:end) zeros(1,matchingdelay)]; mf_pulses = reshape(mf_pulses,sz_mfpulses);

% Pulse integration int_pulses = pulsint(mf_pulses,'noncoherent'); int_pulses = squeeze(int_pulses);

% Visualize r = v*fast_time_grid/2; X = r'*cosd(scangrid); Y = r'*sind(scangrid); clf; pcolor(X,Y,pow2db(abs(int_pulses).^2)); axis equal tight shading interp axis off text(-800,0,'Array'); text((max(r)+10)*cosd(initialAz),(max(r)+10)*sind(initialAz),... [num2str(initialAz) '^o']); text((max(r)+10)*cosd(endAz),(max(r)+10)*sind(endAz),... [num2str(endAz) '^o']); text((max(r)+10)*cosd(0),(max(r)+10)*sind(0),[num2str(0) '^o']); colorbar;

%% % From the scan map, we can clearly see two peaks. The close one is at % around 0 degrees azimuth, the remote one at around 10 degrees in azimuth.

%% Detection and Range Estimation % To obtain an accurate estimation of the target parameters, we apply % threshold detection on the scan map. First we need to compensate for % signal power loss due to range by applying time varying gains to the % received signal.

range_gates = v*fast_time_grid/2; tvg = phased.TimeVaryingGain(... 'RangeLoss',2*fspl(range_gates,lambda),... 'ReferenceLoss',2*fspl(max(range_gates),lambda)); tvg_pulses = tvg(mf_pulses);

% Pulse integration int_pulses = pulsint(tvg_pulses,'noncoherent'); int_pulses = squeeze(int_pulses);

% Calculate the detection threshold

% sample rate is twice the noise bandwidth in the design system noise_bw = receiver.SampleRate/2; npower = noisepow(noise_bw,... receiver.NoiseFigure,receiver.ReferenceTemperature); threshold = npower * db2pow(npwgnthresh(pfa,int_pulsenum,'noncoherent')); % Increase the threshold by the matched filter processing gain threshold = threshold * db2pow(mfgain);

%% % We now visualize the detection process. To better represent the data, we % only plot range samples beyond 50.

N = 51; clf; surf(X(N:end,:),Y(N:end,:),... pow2db(abs(int_pulses(N:end,:)).^2)); hold on; mesh(X(N:end,:),Y(N:end,:),... pow2db(threshold*ones(size(X(N:end,:)))),'FaceAlpha',0.8); view(0,56); axis off

%% % There are two peaks visible above the detection threshold, corresponding % to the two targets we defined earlier. We can find the locations of these % peaks and estimate the range and angle of each target.

[~,peakInd] = findpeaks(int_pulses(:),'MinPeakHeight',sqrt(threshold)); [rngInd,angInd] = ind2sub(size(int_pulses),peakInd); est_range = range_gates(rngInd); % Estimated range est_angle = scangrid(angInd); % Estimated direction

%% Doppler Estimation % Next, we want to estimate the Doppler speed of each target. For details % on Doppler estimation, refer to the example % Doppler Estimation. % for m = numtargets:-1:1 [p, f] = periodogram(mf_pulses(rngInd(m),:,angInd(m)),[],256,prf, ... 'power','centered'); speed_vec = dop2speed(f,lambda)/2;

     spectrum_data = p/max(p);
     [~,dop_detect1] = findpeaks(pow2db(spectrum_data),'MinPeakHeight',-5);
     sp(m) = speed_vec(dop_detect1) % Estimated Doppler speed
end

%% % Finally, we have estimated all the parameters of both detected targets. % Below is a comparison of the estimated and true parameter values.

%% % ------------------------------------------------------------------------ % Estimated (true) target parameters % ------------------------------------------------------------------------ % Range (m) Azimuth (deg) Speed (m/s) % Target 1: 3625.00 (3622.08) 12.00 (12.76) 86.01 (86.49) % Target 2: 2025.00 (2020.66) 0.00 (0.00) -59.68 (-60.00)

%% Summary % In this example, we showed how to simulate a phased array radar to scan a % predefined surveillance region. We illustrated how to design the % scanning schedule. A conventional beamformer was used to process the % received multi-channel signal. The range, angle, and Doppler information % of each target are extracted from the reflected pulses. This information % can be used in further tasks such as high resolution direction-of-arrival % estimation, or target tracking.

displayEndOfDemoMessage(mfilename)

Answer 1

[Honglei Chen]

The line

   sv = steeringvec(fc,scangrid(scanid));

computes the steering weights. If you want to scan elevation domain, just make sure that the scan grid includes the elevation angles you wish to search.

HTH

[Ali Mehdi]

actually i am not able to make scan grid in elevation domain

[Ali Mehdi]

how to make scan grid in elevation domain