tunableProperties
Syntax
Description
specifies if the tracking filters of the tps = tunableProperties(filter,AsParameterizedFilter=asParameterized)trackingGSF
object are parameterized.
Note
Use this syntax only when the filter input is a
trackingGSF object.
Examples
Create a trackingEKF object.
filter = trackingEKF;
Obtain the tunable properties using the tunableProperties object function.
tps = tunableProperties(filter)
tps =
Tunable properties for object of type: trackingEKF
Property: ProcessNoise
PropertyValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunedQuantity: Square root
IsTuned: true
TunedQuantityValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunableElements: [1 5 6 9 10 11 13 14 15 16]
LowerBound: [0 0 0 0 0 0 0 0 0 0]
UpperBound: [10 10 10 10 10 10 10 10 10 10]
Property: StateCovariance
PropertyValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunedQuantity: Square root of initial value
IsTuned: false
Create a trackingUKF object.
filter = trackingUKF;
Obtain the tunable properties using the tunableProperties object function.
tps = tunableProperties(filter)
tps =
Tunable properties for object of type: trackingUKF
Property: ProcessNoise
PropertyValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunedQuantity: Square root
IsTuned: true
TunedQuantityValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunableElements: [1 5 6 9 10 11 13 14 15 16]
LowerBound: [0 0 0 0 0 0 0 0 0 0]
UpperBound: [10 10 10 10 10 10 10 10 10 10]
Property: StateCovariance
PropertyValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunedQuantity: Square root of initial value
IsTuned: false
Property: Alpha
PropertyValue: 0.001
TunedQuantity: Value
IsTuned: true
TunedQuantityValue: 0.001
TunableElements: 1
LowerBound: 1e-05
UpperBound: 1
Property: Beta
PropertyValue: 2
TunedQuantity: Value
IsTuned: false
Property: Kappa
PropertyValue: 0
TunedQuantity: Value
IsTuned: false
Create a trackingIMM object.
filter = trackingIMM;
Obtain the tunable properties using the tunableProperties object function. You can click the links (active in live script) in the display to display the tunable properties of the tracking filters used in the trackingIMM object.
tps = tunableProperties(filter)
tps =
Tunable properties for object of type: trackingIMM
Property: TransitionProbabilities
PropertyValue: [0.9 0.05 0.05;0.05 0.9 0.05;0.05 0.05 0.9]
TunedQuantity: Rows sum to one
IsTuned: true
TunedQuantityValue: [0.9 0.05 0.05;0.05 0.9 0.05;0.05 0.05 0.9]
TunableElements: [1 2 3 4 5 6 7 8 9]
LowerBound: [0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001]
UpperBound: [1 1 1 1 1 1 1 1 1]
Property: ModelProbabilities
PropertyValue: [0.333333333333333;0.333333333333333;0.333333333333333]
TunedQuantity: Columns sum to one
IsTuned: true
TunedQuantityValue: [0.333333333333333;0.333333333333333;0.333333333333333]
TunableElements: [1 2 3]
LowerBound: [0.001 0.001 0.001]
UpperBound: [1 1 1]
The filter contains 3 tracking filters
Show tunable properties for filter 1
Show tunable properties for filter 2
Show tunable properties for filter 3
Create a trackingGSF object.
filter = trackingGSF
filter =
trackingGSF with properties:
State: [4×1 double]
StateCovariance: [4×4 double]
TrackingFilters: {2×1 cell}
HasMeasurementWrapping: [0 0]
ModelProbabilities: [2×1 double]
MeasurementNoise: [3×3 double]
Obtain the tunable properties using the tunableProperties object function. By default, the function assumes the tracking filters of the trackingGSF object are parameterized and share the same models and process noise. Therefore, only the ProcessNoise property is tunable.
tps1 = tunableProperties(filter)
tps1 =
Tunable properties for object of type: trackingGSF
Property: ProcessNoise
PropertyValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunedQuantity: Square root
IsTuned: true
TunedQuantityValue: [1 0 0 0;0 1 0 0;0 0 1 0;0 0 0 1]
TunableElements: [1 5 6 9 10 11 13 14 15 16]
LowerBound: [0 0 0 0 0 0 0 0 0 0]
UpperBound: [10 10 10 10 10 10 10 10 10 10]
Set the AsParameterizedFilter argument to false, which allows the tuner to tune each tracking filter individually.
tps2 = tunableProperties(filter,AsParameterizedFilter=false)
tps2 =
Tunable properties for object of type: trackingGSF
Property: ModelProbabilities
PropertyValue: [0.5;0.5]
TunedQuantity: Columns sum to one
IsTuned: true
TunedQuantityValue: [0.5;0.5]
TunableElements: [1 2]
LowerBound: [0.001 0.001]
UpperBound: [1 1]
The filter contains 2 tracking filters
Show tunable properties for filter 1
Show tunable properties for filter 2
Input Arguments
Tracking filter, specified as one of these objects:
Indicate if the tracking filters of the trackingGSF
object are parameterized, specified as true or
false.
true(default) — ThetrackingFilterTunerobject treats the tracking filters in theTrackingFiltersproperty of thetrackingGSFobject as a set of parameterized filters and assumes that these tracking filters have the same target process model. Therefore, the tuner assumes these tracking filters share the same process noise matrix and only tunes this matrix.false— ThetrackingFilterTunerobject tunes each tracking filter in theTrackingFiltersproperty of thetrackingGSFobject individually. In this case, the tuner tunes theModelProbabilitiesproperty of thetrackingGSFobject and the tunable properties of each tracking filter.
Tip
You can use the setPropertyTunability object function of the tunableFilterProperties object to further custom the tunable properties
and tunable elements.
Output Arguments
Tunable properties, returned as a tunableFilterProperties object.
Version History
Introduced in R2022b
MATLAB Command
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