tunableFilterProperties
Description
The tunableFilterProperties
object defines the tunable properties of a
tracking filter object. To specify the properties to tune and how to tune them, use the
setPropertyTunability
object function. To tune the filter, create a trackingFilterTuner
object and use the tune
object
function.
Creation
Create a tunableFilterProperties
object by using the tunableProperties
object function of a tunable tracking filter. The tunable tracking filters are:
Object Functions
setPropertyTunability | Modify property tunability |
Examples
Create a trackingEKF
object using the initcvekf
function.
filter = initcvekf(objectDetection(0,[0;0;0]));
Obtain the tunable properties of the filter using the tunableProperties
object function.
tps = tunableProperties(filter)
tps = Tunable properties for object of type: trackingEKF Property: ProcessNoise PropertyValue: [1 0 0;0 1 0;0 0 1] TunedQuantity: Square root IsTuned: true TunedQuantityValue: [1 0 0;0 1 0;0 0 1] TunableElements: [1 4 5 7 8 9] LowerBound: [0 0 0 0 0 0] UpperBound: [10 10 10 10 10 10] Property: StateCovariance PropertyValue: [1 0 0 0 0 0;0 100 0 0 0 0;0 0 1 0 0 0;0 0 0 100 0 0;0 0 0 0 1 0;0 0 0 0 0 100] TunedQuantity: Square root of initial value IsTuned: false
From the display, the ProcessNoise
property is tuned and the StateCovariance
property is not tuned by default.
Set the StateCovariance
property as tuned.
setPropertyTunability(tps,"StateCovariance",IsTuned=true);
disp(tps);
Tunable properties for object of type: trackingEKF Property: ProcessNoise PropertyValue: [1 0 0;0 1 0;0 0 1] TunedQuantity: Square root IsTuned: true TunedQuantityValue: [1 0 0;0 1 0;0 0 1] TunableElements: [1 4 5 7 8 9] LowerBound: [0 0 0 0 0 0] UpperBound: [10 10 10 10 10 10] Property: StateCovariance PropertyValue: [1 0 0 0 0 0;0 100 0 0 0 0;0 0 1 0 0 0;0 0 0 100 0 0;0 0 0 0 1 0;0 0 0 0 0 100] TunedQuantity: Square root of initial value IsTuned: true TunedQuantityValue: [1 0 0 0 0 0;0 10 0 0 0 0;0 0 1 0 0 0;0 0 0 10 0 0;0 0 0 0 1 0;0 0 0 0 0 10] TunableElements: [1 7 8 13 14 15 19 20 21 22 25 26 27 28 29 31 32 33 34 35 36] LowerBound: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] UpperBound: [100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100]
Set the tuned elements for the process noise matrix as the diagonal elements with specified bounds. Also, set the tuned elements for the state covariance matrix as the diagonal elements with specified bounds.
setPropertyTunability(tps,"ProcessNoise",TunableElements=sub2ind([3,3],[1 2 3],[1 2 3]), ... LowerBound=[0 0 0],UpperBound=[10 10 10]); setPropertyTunability(tps,"StateCovariance",TunableElements=sub2ind([6,6],1:6,1:6), ... LowerBound=zeros(1,6),UpperBound=100*ones(1,6)); disp(tps)
Tunable properties for object of type: trackingEKF Property: ProcessNoise PropertyValue: [1 0 0;0 1 0;0 0 1] TunedQuantity: Square root IsTuned: true TunedQuantityValue: [1 0 0;0 1 0;0 0 1] TunableElements: [1 5 9] LowerBound: [0 0 0] UpperBound: [10 10 10] Property: StateCovariance PropertyValue: [1 0 0 0 0 0;0 100 0 0 0 0;0 0 1 0 0 0;0 0 0 100 0 0;0 0 0 0 1 0;0 0 0 0 0 100] TunedQuantity: Square root of initial value IsTuned: true TunedQuantityValue: [1 0 0 0 0 0;0 10 0 0 0 0;0 0 1 0 0 0;0 0 0 10 0 0;0 0 0 0 1 0;0 0 0 0 0 10] TunableElements: [1 8 15 22 29 36] LowerBound: [0 0 0 0 0 0] UpperBound: [100 100 100 100 100 100]
Create a trackingUKF
object using the initcvukf
function.
filter = initcvukf(objectDetection(0,[0;0;0]));
Obtain the tunable properties of the filter using the tuanbleProperties
object function.
tps = tunableProperties(filter)
tps = Tunable properties for object of type: trackingUKF Property: ProcessNoise PropertyValue: [1 0 0;0 1 0;0 0 1] TunedQuantity: Square root IsTuned: true TunedQuantityValue: [1 0 0;0 1 0;0 0 1] TunableElements: [1 4 5 7 8 9] LowerBound: [0 0 0 0 0 0] UpperBound: [10 10 10 10 10 10] Property: StateCovariance PropertyValue: [1 0 0 0 0 0;0 100 0 0 0 0;0 0 1 0 0 0;0 0 0 100 0 0;0 0 0 0 1 0;0 0 0 0 0 100] 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
From the display, the ProcessNoise
property is tuned and the StateCovariance
property is not tuned by default.
Set the Beta
property as tuned.
setPropertyTunability(tps,"Beta",IsTuned=true);
disp(tps);
Tunable properties for object of type: trackingUKF Property: ProcessNoise PropertyValue: [1 0 0;0 1 0;0 0 1] TunedQuantity: Square root IsTuned: true TunedQuantityValue: [1 0 0;0 1 0;0 0 1] TunableElements: [1 4 5 7 8 9] LowerBound: [0 0 0 0 0 0] UpperBound: [10 10 10 10 10 10] Property: StateCovariance PropertyValue: [1 0 0 0 0 0;0 100 0 0 0 0;0 0 1 0 0 0;0 0 0 100 0 0;0 0 0 0 1 0;0 0 0 0 0 100] 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: true TunedQuantityValue: 2 TunableElements: 1 LowerBound: 0 UpperBound: Inf Property: Kappa PropertyValue: 0 TunedQuantity: Value IsTuned: false
Set the tuned elements for the process noise matrix as the diagonal elements with specified bounds.
setPropertyTunability(tps,"ProcessNoise",TunableElements=sub2ind([3,3],[1 2 3],[1 2 3]), ... LowerBound=[0 0 0],UpperBound=[10 10 10]); disp(tps)
Tunable properties for object of type: trackingUKF Property: ProcessNoise PropertyValue: [1 0 0;0 1 0;0 0 1] TunedQuantity: Square root IsTuned: true TunedQuantityValue: [1 0 0;0 1 0;0 0 1] TunableElements: [1 5 9] LowerBound: [0 0 0] UpperBound: [10 10 10] Property: StateCovariance PropertyValue: [1 0 0 0 0 0;0 100 0 0 0 0;0 0 1 0 0 0;0 0 0 100 0 0;0 0 0 0 1 0;0 0 0 0 0 100] 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: true TunedQuantityValue: 2 TunableElements: 1 LowerBound: 0 UpperBound: Inf Property: Kappa PropertyValue: 0 TunedQuantity: Value IsTuned: false
Create a trackingIMM
object using the initekfimm
function.
filter = initekfimm(objectDetection(0,[0;0;0]));
Obtain the tunable properties of the filter using the tuanbleProperties
object function.
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
Set the ModelProbabilities
property to untuned.
setPropertyTunability(tps,"ModelProbabilities",IsTuned=false);
disp(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: false The filter contains 3 tracking filters Show tunable properties for filter 1 Show tunable properties for filter 2 Show tunable properties for filter 3
Set the tuned elements for the process noise matrices in the three trackingEKF
objects. In this example, set the tunable elements as the diagonal elements with specified bounds.
setPropertyTunability(tps,"ProcessNoise",FilterIndex=1,TunableElements=sub2ind([3,3],[1 2 3],[1 2 3]), ... LowerBound=[0 0 0],UpperBound=[10 10 10]); setPropertyTunability(tps,"ProcessNoise",FilterIndex=2,TunableElements=sub2ind([3,3],[1 2 3],[1 2 3]), ... LowerBound=[0 0 0],UpperBound=[10 10 10]); setPropertyTunability(tps,"ProcessNoise",FilterIndex=3,TunableElements=sub2ind([3,3],[1 2 3],[1 2 3]), ... LowerBound=[0 0 0],UpperBound=[10 10 10]);
Version History
Introduced in R2022b
See Also
tunableProperties
| setTunedProperties
| trackingFilterTuner
MATLAB Command
You clicked a link that corresponds to this MATLAB command:
Run the command by entering it in the MATLAB Command Window. Web browsers do not support MATLAB commands.
选择网站
选择网站以获取翻译的可用内容,以及查看当地活动和优惠。根据您的位置,我们建议您选择:。
您也可以从以下列表中选择网站:
如何获得最佳网站性能
选择中国网站(中文或英文)以获得最佳网站性能。其他 MathWorks 国家/地区网站并未针对您所在位置的访问进行优化。
美洲
- América Latina (Español)
- Canada (English)
- United States (English)
欧洲
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)