trackingSensorConfiguration

Represent sensor configuration for tracking

Description

The trackingSensorConfiguration object creates the configuration for a sensor used with a trackerPHD System object™. It allows you to specify the sensor parameters such as clutter density, sensor limits, sensor resolution. You can also specify how a tracker perceives the detections from the sensor using properties such as FilterInitializationFcn, SensorTransformFcn, and SensorTransformParameters. See Create a Tracking Sensor Configuration for more details. The trackingSensorConfiguration object enables the tracker to perform three main routine operations:

Evaluate the probability of detection at points in state-space.
Initiate components in the probability hypothesis density.
Obtain the clutter density of the sensor.

Creation

Syntax

config = trackingSensorConfiguration(SensorIndex)

config = trackingSensorConfiguration(SensorIndex,Name,Value)

Description

config = trackingSensorConfiguration(SensorIndex) creates a trackingSensorConfiguration object with a specified sensor index, SensorIndex, and default property values.

example

config = trackingSensorConfiguration(SensorIndex,Name,Value) allows you to set properties using one or more name-value pairs.

Properties

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`SensorIndex` — Unique sensor identifier
positive integer

Unique sensor identifier, specified as a positive integer. This property distinguishes detections that come from different sensors in a multi-sensor system. When creating a trackingSensorConfiguration object, you must specify the SensorIndex as the first input argument in the creation syntax.

Example: 2

Data Types: double

`IsValidTime` — Indicate detection reporting status
`false` (default) | `true`

Indicate the detection reporting status of the sensor, specified as false or true. Set this property to true when the sensor must report detections within its sensor limits to the tracker. If a track or target was supposed to be detected by a sensor but the sensor reported no detections, then this information is used to count against the probability of existence of the track when the isValidTime property is set to true.

Data Types: logical

`FilterInitializationFcn` — Filter initialization function
`@initcvggiwphd` (default) | function handle | character vector

Filter initialization function, specified as a function handle or as a character vector containing the name of a valid filter initialization function. The function initializes the PHD filter used by trackerPHD. The function must support the following syntaxes:

filter = filterInitializationFcn()
filter = filterInitializationFcn(detections)

filter is a valid PHD filter with components for new-born targets, and detections is a cell array of objectDetection objects. The first syntax allows you to specify the predictive birth density in the PHD filter without using detections. The second syntax allows the filter to initialize the adaptive birth density using detection information. See the BirthRate property of trackerPHD for more details. If you create your own FilterInitilizationFcn, you must also provide a transform function using the SensorTransformFcn property. Other than the default filter initialization function initcvggiwphd, Sensor Fusion and Tracking Toolbox™ also provides other initialization functions, such as initctrectgmphd, initctgmphd, initcvgmphd, initcagmphd, initctggiwphd and initcaggiwphd.

Data Types: function_handle | char

`SensorTransformFcn` — Sensor transform function
`@cvmeas` | function handle | character vector

Sensor transform function, specified as a function handle or as a character vector containing the name of a valid sensor transform function. The function transforms a track's state into the sensor's detection state. For example, the function transforms the track's state in the scenario Cartesian frame to the sensor's spherical frame. You can create your own sensor transform function, but it must support the following syntax:

detStates = SensorTransformFcn(trackStates,params)

params are the parameters stored in the SensorTransformParameters property. Notice that the signature of the function is similar to a measurement function. Therefore, you can use a measurement function (such as cvmeas, ctmeas, or cameas) as the SensorTransformFcn.

Depending on the filter type and the target type, the output, detStates, needs to return differently.

When used with gmphd for non-extended targets or with ggiwphd, detStates is a N-by-M matrix, where N is the number of rows in the SensorLimits property and M is the number of input states in trackStates. For gmphd, non-extended targets refer to point targets and extended targets whose MeasurementOrigin is 'center'.
When used with gmphd for extended targets, the SensorTransformFcn allows you to specify multiple detStates per trackState. In this case, detStates is a N-by-M-by-S matrix, where S is the number of detectable sources on the extended target. For example, if the target is described by a rectangular state, the detectable sources can be the corners of the rectangle.
If any of the source falls inside the SensorLimits, the target is declared detectable. The functions uses the spread (maximum coordinate − minimum coordinate) of each detStates and the ratio between the spread and sensor resolution on each sensor limit to calculate the expected number of detections from each extended target. You can override this default setting by providing an optional output in the SensorTransformFcn as:
```
[..., Nexp] = SensorTransformFcn(trackStates, params)
```
where Nexp is the expected number of detections from each extended track state.

Note that the default SensorTransformFcn is the sensor transform function of the filter returned by FilterInitilizationFcn. For example, the initicvggiwphd function returns the default cvmeas, whereas initictggiwphd and initicaggiwphd functions return ctmeas and cameas, respectively.

Data Types: function_handle | char

`SensorTransformParameters` — Parameters for sensor transform function
structure | array of structures

Parameters for the sensor transform function, returned as a structure or an array of structures. If you only need to transform the state once, specify it as a structure. If you need to transform the state n times, specify it as an n-by-1 array of structures. For example, to transform a state from the scenario frame to the sensor frame, you usually need to first transform the state from the scenario rectangular frame to the platform rectangular frame, and then transform the state from the platform rectangular frame to the sensor spherical frame. The fields of the structure are:

Field	Description
`Frame`	Child coordinate frame type, specified as `'Rectangular'` or `'Spherical'`.
`OriginPosition`	Child frame origin position expressed in the Parent frame, specified as a 3-by-1 vector.
`OriginVelocity`	Child frame origin velocity expressed in the parent frame, specified as a 3-by-1 vector.
`Orientation`	Relative orientation between frames, specified as a 3-by-3 rotation matrix. If the `IsParentToChild` property is set to `false`, then specify `Orientation` as the rotation from the child frame to the parent frame. If the `IsParentToChild` property is set to `true`, then specify `Orientation` as the rotation from the parent frame to the child frame.
`IsParentToChild`	Flag to indicate the direction of rotation between parent and child frame, specified as `true` or `false`. The default is `false`. See description of the `Orientation` field for details.
`HasAzimuth`	Indicates whether outputs contain azimuth components, specified as `true` or `false`.
`HasElevation`	Indicates whether outputs contain elevation components, specified as `true` or `false`.
`HasRange`	Indicates whether outputs contain range components, specified as `true` or `false`.
`HasVelocity`	Indicates whether outputs contains velocity components, specified as `true` or `false`.

Note that here the scenario frame is the parent frame of the platform frame, and the platform frame is the parent frame of the sensor frame.

The default values for SensorTransformParameters are a 2-by-1 array of structures as:

Fields	Struct 1	Struct 2
Frame	`'Spherical'`	`'Rectangular'`
OriginPosition	`[0;0;0]`	`[0;0;0]`
OriginVelocity	`[0;0;0]`	`[0;0;0]`
Orientation	`eye(3)`	`eye(3)`
IsParentToChild	`false`	`false`
HasAzimuth	`true`	`true`
HasElevation	`true`	`true`
HasRange	`true`	`true`
HasVelocity	`false`	`true`

In this table, Struct 2 accounts for the transformation from the scenario rectangular frame to the platform rectangular frame, and Struct 1 accounts for the transformation from the platform rectangular frame to the sensor spherical frame, given the isParentToChild property is set to false.

Data Types: struct

`SensorLimits` — Sensor's detection limits
3-by-2 matrix (default) | N-by-2 matrix

Sensor's detection limits, specified as an N-by-2 matrix, where N is the output dimension of the sensor transform function. The matrix must describe the lower and upper detection limits of the sensor in the same order as the outputs of the sensor transform function.

If you use cvmeas, cameas, or ctmeas as the sensor transform function, then you need to provide the sensor limits in order as:

$SensorLimits = [\begin{matrix} minAz & maxAz \\ minEl & maxEl \\ minRng & maxRng \\ minRr & maxRr \end{matrix}]$

The description of these limits and their default values are given in the following table. Note that the default values for SensorLimits are a 3-by-2 matrix including the top six elements in the table. Moreover, if you use these three functions, you can specify the matrix to be in other sizes (1-by-2, 2-by-2, or 3-by-4), but you have to specify these limits in the sequence shown in the SensorLimits matrix.

Limits	Description	Default values
minAz	Minimum detectable azimuth in degrees.	`-10`
maxAz	Maximum detectable azimuth in degrees.	`10`
minEl	Minimum detectable elevation in degrees.	`-2.5`
maxEl	Maximum detectable elevation in degrees.	`2.5`
minRng	Minimum detectable range in meters.	`0`
maxRng	Maximum detectable range in meters.	`1000`
minRr	Minimum detectable range rate in meters per second.	N/A
maxRr	Maximum detectable range rate in meters per second.	N/A

Data Types: double

`SensorResolution` — Resolution of sensor
`[4;2;10]` (default) | N-element positive-valued vector

Resolution of a sensor, specified as a N-element positive-valued vector, where N is the number of parameters specified in the SensorLimits property. If you want to assign only one resolution cell for a parameter, simply specify its resolution as the difference between the maximum limit and the minimum limit of the parameter.

Data Types: double

`MaxNumDetsPerObject` — Maximum number of detections per object
`Inf` (default) | positive integer

Maximum number of detections the sensor can report per object, specified as a positive integer.

Example: 3

Data Types: double

`ClutterDensity` — Expected number of false alarms per unit volume
`1e-3` (default) | positive scalar

Expected number of false alarms per unit volume from the sensor, specified as a positive scalar.

Example: 2e-3

Data Types: double

`MinDetectionProbability` — Probability of detecting track estimated to be outside of sensor limits
`0.05` (default) | positive scalar

Probability of detecting a target estimated to be outside of the sensor limits, specified as a positive scalar. This property allows a trackerPHD object to consider that the estimated target, which is outside the sensor limits, may be detectable.

Example: 0.03

Data Types: double

Examples

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Create Radar Sensor Configuration

Open Live Script

Consider a radar with the following sensor limits and sensor resolution.

  azLimits = [-10 10];
  elLimits = [-2.5 2.5];
  rangeLimits = [0 500];
  rangeRateLimits = [-50 50];
  sensorLimits = [azLimits;elLimits;rangeLimits;rangeRateLimits];
  sensorResolution = [5 2 10 3];

Specifying the sensor transform function that transforms the Cartesian coordinates [x;y;vx;vy] in the scenario frame to the spherical coordinates [az;el;range;rr] in the sensor's frame. You can use the measurement function cvmeas as the sensor transform function.

  transformFcn = @cvmeas;

To specify the parameters required for cvmeas, use the SensorTransformParameters property. Here, you assume the sensor is mounted at the center of the platform and the platform located at [100;30;20] is moving with a velocity of [-5;4;2] units per second in the scenario frame.

The first structure defines the sensor's location, velocity, and orientation in the platform frame.

  params(1) = struct('Frame','Spherical','OriginPosition',[0;0;0],...
                   'OriginVelocity',[0;0;0],'Orientation',eye(3),'HasRange',true,...
                   'HasVelocity',true);

The second structure defines the platform's location, velocity, and orientation in the scenario frame.

  params(2) = struct('Frame','Rectangular','OriginPosition',[100;30;20],...
                    'OriginVelocity',[-5;4;2],'Orientation',eye(3),'HasRange',true,...
                    'HasVelocity',true);

Create the configuration.

  config = trackingSensorConfiguration('SensorIndex',3,'SensorLimits',sensorLimits,...
                                       'SensorResolution',sensorResolution,...
                                       'SensorTransformParameters',params,...
                                       'SensorTransformFcn',@cvmeas,...
                                       'FilterInitializationFcn',@initcvggiwphd)

config = 
  trackingSensorConfiguration with properties:

                  SensorIndex: 3
                  IsValidTime: 0

                 SensorLimits: [4x2 double]
             SensorResolution: [4x1 double]
           SensorTransformFcn: @cvmeas
    SensorTransformParameters: [1x2 struct]

      FilterInitializationFcn: @initcvggiwphd
          MaxNumDetsPerObject: Inf

               ClutterDensity: 1.0000e-03
         DetectionProbability: 0.9000
      MinDetectionProbability: 0.0500

More About

expand all

Create a Tracking Sensor Configuration

To create the configuration for a sensor, you first need to specify the sensor transform function, which is usually given as:

$Y = g (x, p)$

where x denotes the tracking state, Y denotes detection states, and p denotes the required parameters. For object tracking applications, you mainly focus on obtaining an object's tracking state. For example, a radar sensor can measure an object's azimuth, elevation, range, and possibly range-rate. Using a trackingSensorConfiguration object, you can specify a radar's transform function using the SensorTransformFcn property and specify the radar's mounting location, orientation, and velocity using corresponding fields in the SensorTransformParameters property. If the object is moving at a constant velocity, constant acceleration, or constant turning, you can use the built-in measurement function – cvmeas, cameas, or ctmeas, respectively – as the SensorTransformFcn. To set up the exact outputs of these three functions, specify the hasAzimuth, hasElevation, hasRange, and hasVelocity fields as true or false in the SensorTransformParameters property.

To set up the configuration of a sensor, you also need to specify the sensor's detection ability. Primarily, you need to specify the sensor's detection limits. For all the outputs of the sensor transform function, you need to provide the detection limits in the same order of these outputs using the SensorLimits property. For example, for a radar sensor, you might need to provide its azimuth, elevation, range, and range-rate limits. You can also specify the radar's SensorResolution and MaxNumDetsPerObject properties if you want to consider extended object detection. You might also want to specify other properties, such as ClutterDensity, IsValidTime, and MinDetectionProbability to further clarify the sensor's detection ability.

Documentation

trackingSensorConfiguration

Description

Creation

Syntax

Description

Properties

`SensorIndex` — Unique sensor identifier
positive integer

`IsValidTime` — Indicate detection reporting status
`false` (default) | `true`

`FilterInitializationFcn` — Filter initialization function
`@initcvggiwphd` (default) | function handle | character vector

`SensorTransformFcn` — Sensor transform function
`@cvmeas` | function handle | character vector

`SensorTransformParameters` — Parameters for sensor transform function
structure | array of structures

`SensorLimits` — Sensor's detection limits
3-by-2 matrix (default) | N-by-2 matrix

`SensorResolution` — Resolution of sensor
`[4;2;10]` (default) | N-element positive-valued vector

`MaxNumDetsPerObject` — Maximum number of detections per object
`Inf` (default) | positive integer

`ClutterDensity` — Expected number of false alarms per unit volume
`1e-3` (default) | positive scalar

`MinDetectionProbability` — Probability of detecting track estimated to be outside of sensor limits
`0.05` (default) | positive scalar

Examples

Create Radar Sensor Configuration

More About

Create a Tracking Sensor Configuration

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

See Also

Sensor Fusion and Tracking Toolbox Documentation

Support

Documentation

trackingSensorConfiguration

Description

Creation

Syntax

Description

Properties

SensorIndex — Unique sensor identifier positive integer

IsValidTime — Indicate detection reporting status false (default) | true

FilterInitializationFcn — Filter initialization function @initcvggiwphd (default) | function handle | character vector

SensorTransformFcn — Sensor transform function @cvmeas | function handle | character vector

SensorTransformParameters — Parameters for sensor transform function structure | array of structures

SensorLimits — Sensor's detection limits 3-by-2 matrix (default) | N-by-2 matrix

SensorResolution — Resolution of sensor [4;2;10] (default) | N-element positive-valued vector

MaxNumDetsPerObject — Maximum number of detections per object Inf (default) | positive integer

ClutterDensity — Expected number of false alarms per unit volume 1e-3 (default) | positive scalar

MinDetectionProbability — Probability of detecting track estimated to be outside of sensor limits 0.05 (default) | positive scalar

Examples

Create Radar Sensor Configuration

More About

Create a Tracking Sensor Configuration

Extended Capabilities

C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™.

See Also

Sensor Fusion and Tracking Toolbox Documentation

Support

`SensorIndex` — Unique sensor identifier
positive integer

`IsValidTime` — Indicate detection reporting status
`false` (default) | `true`

`FilterInitializationFcn` — Filter initialization function
`@initcvggiwphd` (default) | function handle | character vector

`SensorTransformFcn` — Sensor transform function
`@cvmeas` | function handle | character vector

`SensorTransformParameters` — Parameters for sensor transform function
structure | array of structures

`SensorLimits` — Sensor's detection limits
3-by-2 matrix (default) | N-by-2 matrix

`SensorResolution` — Resolution of sensor
`[4;2;10]` (default) | N-element positive-valued vector

`MaxNumDetsPerObject` — Maximum number of detections per object
`Inf` (default) | positive integer

`ClutterDensity` — Expected number of false alarms per unit volume
`1e-3` (default) | positive scalar

`MinDetectionProbability` — Probability of detecting track estimated to be outside of sensor limits
`0.05` (default) | positive scalar

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.