# 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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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`

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`

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`

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`

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`

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:

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`

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`

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

Example: `3`

Data Types: `double`

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

Example: `2e-3`

Data Types: `double`

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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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 ```

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