Generate Code with Strict Single-Precision and Non-Dynamic Memory Allocation

Introduce functions, objects, and blocks that support strict single-precision and non-dynamic memory allocation code generation in Sensor Fusion and Tracking Toolbox™.

Introduction to Strict Single-Precision and Non-Dynamic Memory Allocation

In Sensor Fusion and Tracking Toolbox (SFTT), many functions, objects, and Simulink blocks support C/C++ code generation. You can see if a function, object, or block supports code generation, as well as any limitations in the Extended Capabilities section of its reference page. For details on how to generate code at the command line, or by using the MATLAB^® Coder™ App, see Generate C Code at the Command Line (MATLAB Coder) and Generate C Code by Using the MATLAB Coder App (MATLAB Coder), respectively. For generating code for SFTT applications, see these examples:

• How to Generate C Code for a Tracker

• Generate Code for a Track Fuser with Heterogeneous Source Tracks

• Processor-in-the-Loop Verification of JPDA Tracker for Automotive Applications

Sensor Fusion and Tracking Toolbox widely supports double-precision code generation, and the generated code can use dynamic memory allocation if necessary. Though double-precision variables can provide more accurate calculations, they have increased memory requirements over single-precision variables. Similarly, though dynamic memory allocation allows for flexible variable allocation, this process is typically slower than non-dynamic memory allocation. For these and other reasons, Sensor Fusion and Tracking Toolbox provides strict single-precision and non-dynamic memory allocation support for some algorithms.

In strict single-precision code generation, the generated C/C++ code, including the input, code body, and output, does not use double-precision variables. In other words, it can only use single-precision variables and integer-type variables up to 32 bits. For algorithms that support strict single-precision code generation in SFTT, you can enable it by passing single-precision input arguments. To enable strict single-precision code generation:

• For a function that supports strict single-precision code generation, specify single-precision inputs.

• For an object that supports strict single-precision code generation, specify the inputs as non-double-precision variables, and specify any custom setups as non-double precision. For example, to generate single-precision code from the trackerGNN System object™:

  • You must specify the inputs, such as the detections, as non-double-precision values.

  • You must specify the FilterInitializationFcn property of the tracker to return a single-precision filter.

In non-dynamic memory allocation code generation, the memory allocation of each variable is determined during compilation time, before running the code. Non-dynamic memory allocation is usually faster than dynamic memory allocation. For information on how to disable dynamic memory allocation, see Generate Code for Variable-Size Data (MATLAB Coder) and Control Memory Allocation for Variable-Size Arrays (MATLAB Coder).

The functions, objects, and blocks listed in the table of the following sections are verified to support strict single-precision and non-dynamic memory allocation code generation. Other unverified functions, object, and blocks in SFTT can possibly support strict single-precision and non-dynamic memory allocation.

Supported Trackers and Tracking Filters

These trackers and tracking filters support strict single-precision and non-dynamic memory allocation code generation with the specified limitations.

Objects or Blocks	Strict single-Precision Code Generation Limitations	Non-Dynamic Memory Allocation Code Generation Limitations
trackerJPDA or Joint Probabilistic Data Association Multi Object Tracker	Must set the tracker to the K-best JPDA mode. Filter must be one of these, configured in single-precision: trackingKF trackingEKF trackingUKF trackingCKF trackingIMM	Must set the tracker to the K-best JPDA mode. Filter must be one of these: trackingKF trackingEKF trackingUKF trackingCKF trackingIMM For trackerJPDA, the MaxNumDetections property must be finite.
trackerGNN or Global Nearest Neighbor Multi Object Tracker	Filter must be one of these, configured in single-precision: trackingKF trackingEKF trackingUKF trackingCKF trackingIMM Assignment algorithm must be Jonker-Volgenant.	Filter must be one of these: trackingKF trackingEKF trackingUKF trackingCKF trackingIMM Assignment algorithm must be Jonker-Volgenant or MatchPairs. For trackerGNN, the MaxNumDetections property must be finite.
trackerPHD or Probability Hypothesis Density (PHD) Tracker	You must specify the filter initialization function as single-precision in each trackingSensorConfiguration object. The filter specified in each trackingSensorConfiguration object must use state transition and measurement functions that support single-precision.	You must specify the MaxNumDetections and MaxNumDetsPerObject properties in each trackingSensorConfiguration object as finite integers.
trackingKF	No limitations	No limitations
trackingEKF	The state transition function and measurement function must support single-precision.	No limitations
trackingUKF	The state transition function and measurement function must support single-precision.	No limitations
trackingCKF	The state transition function and measurement function must support single-precision.	No limitations
trackingIMM	The trackingIMM filter must be configured with either trackingKF, trackingEKF, trackingUKF, or trackingCKF objects set in single-precision.	The trackingIMM filter must be configured with either trackingKF, trackingEKF, trackingUKF, or trackingCKF objects.
gmphd	The motion model and measurement model used in the filter must support single-precision.	No limitations
ggiwphd	The motion model and measurement model used in the filter must support single-precision.	No limitations

Supported Assignment and Partition Functions

These assignment functions support strict single-precision and non-dynamic memory allocation code generation with the specified limitations.

Functions	Strict Single-Precision Code Generation Limitations	Non-Dynamic Memory Allocation Code Generation Limitations
assignkbest	Must use the Jonker-Volgenant algorithm.	Must use the Jonker-Volgenant algorithm.
assignjv	No limitations	No limitations
jpdaEvents	Must use K-best joint event.	Must use K-best joint event.
partitionDetections	No limitations	No limitations
mergeDetections	No limitations	No limitations

Supported Motion Model Functions

These motion model functions support strict single-precision and non-dynamic memory allocation code generation without limitations.

• constvel

• constveljac

• cvmeas

• cvmeasjac

• constacc

• constaccjac

• cameas

• cameasjac

• constturn

• constturnjac

• ctmeas

• ctmeasjac

• switchimm

• ctrect

• ctrectjac

• ctrectmeas

• ctrectmeasjac

Supported Filter Initialization Functions

These filter initialization functions support single-precision and non-dynamic memory allocation code generation without limitations.

• initcvkf

• initcakf

• initcvekf

• initcaekf

• initctekf

• initcvukf

• initcaukf

• initctukf

• initcvckf

• initctckf

• initcackf

• initekfimm

• initcvggiwphd

• initcaggiwphd

• initctggiwphd

• initcvgmphd

• initcagmphd

• initctgmphd

• initctrectgmphd