Detection Concatenation

Combine detection reports from different sensors

• Library:

• Automated Driving Toolbox

  Sensor Fusion and Tracking Toolbox / Utilities

• 

Description

The Detection Concatenation block combines detection reports from multiple sensors onto a single output bus. Concatenation is useful when detections from multiple sensor blocks are passed into a tracker block such as the Multi-Object Tracker block. You can accommodate additional sensors by changing the Number of input sensors to combine parameter to increase the number of input ports.

Ports

Input

In1, In2, ..., InN — Sensor detections to combine

Simulink^® buses containing MATLAB^® structures

Sensor detections to combine, where each detection is a Simulink bus containing a MATLAB structure. See Create Nonvirtual Buses (Simulink) for more details.

The structure has the form:

Field	Description	Type
NumDetections	Number of detections	integer
Detections	Object detections	Array of object detection structures. The first NumDetections of these detections are actual detections.

The fields of Detections are:

Field	Description	Type
Time	Measurement time	single or double
Measurement	Object measurements	single or double
MeasurementNoise	Measurement noise covariance matrix	single or double
SensorIndex	Unique ID of the sensor	single or double
ObjectClassID	Object classification ID	single or double
MeasurementParameters	Parameters used by initialization functions of tracking filters	Simulink Bus
ObjectAttributes	Additional information passed to tracker	Simulink Bus

By default, the block includes two ports for input detections. To add more ports, use the Number of input sensors to combine parameter.

Output

Out — Combined sensor detections

Simulink bus containing MATLAB structure

Combined sensor detections from all input buses, returned as a Simulink bus containing a MATLAB structure. See Create Nonvirtual Buses (Simulink).

The structure has the form:

Field	Description	Type
NumDetections	Number of detections	integer
Detections	Object detections	Array of object detection structures. The first NumDetections of these detections are actual detections.

The fields of Detections are:

Field	Description	Type
Time	Measurement time	single or double
Measurement	Object measurements	single or double
MeasurementNoise	Measurement noise covariance matrix	single or double
SensorIndex	Unique ID of the sensor	single or double
ObjectClassID	Object classification ID	single or double
MeasurementParameters	Parameters used by initialization functions of tracking filters	Simulink Bus
ObjectAttributes	Additional information passed to tracker	Simulink Bus

The Maximum number of reported detections output is the sum of the Maximum number of reported detections of all input ports. The number of actual detections is the sum of the number of actual detections in each input port. The ObjectAttributes fields in the detection structure are the union of the ObjectAttributes fields in each input port.

Parameters

Number of input sensors to combine — Number of input sensor ports

2 (default) | positive integer

Number of input sensor ports, specified as a positive integer. Each input port is labeled In1, In2, …, InN, where N is the value set by this parameter.

Data Types: double

Source of output bus name — Source of output bus name

Auto (default) | Property

Source of output bus name, specified as Auto or Property.

• If you select Auto, the block automatically generates a bus name.

• If you select Property, specify the bus name using the Specify an output bus name parameter.

Specify an output bus name — Name of output bus

no default

Dependencies

To enable this parameter, set the Source of output bus name parameter to Property.

Simulate using — Type of simulation to run

Interpreted execution (default) | Code generation

• Interpreted execution — Simulate the model using the MATLAB interpreter. This option shortens startup time. In Interpreted execution mode, you can debug the source code of the block.

• Code generation — Simulate the model using generated C/C++ code. The first time you run a simulation, Simulink generates C/C++ code for the block. The C code is reused for subsequent simulations as long as the model does not change. This option requires additional startup time.

Model Examples

Sensor Fusion Using Synthetic Radar and Vision Data in Simulink

Implement a synthetic data simulation for tracking and sensor fusion in Simulink with Automated Driving Toolbox™.

Adaptive Cruise Control with Sensor Fusion

Implement an automotive adaptive cruise controller using sensor fusion.

Extended Capabilities

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