Track-To-Track Fuser

Track-to-Track Fusion

Since R2021a

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Libraries:
Sensor Fusion and Tracking Toolbox / Multi-Object Tracking Algorithms

Description

The Track-to-Track Fuser Simulink^® block is a multi-source, multi-object, track-level fuser that uses the global nearest neighbor (GNN) association to maintain a single hypothesis about the tracks it fuses. The inputs to the block are tracks from sources that already track multiple objects, like multi-object tracker blocks or other track-to-track fuser blocks. The input tracks are called source or local tracks, whereas the tracks maintained in the fuser are called central tracks.

Examples

Track-to-Track Fusion for Automotive Safety Applications in Simulink

Perform track-to-track fusion in Simulink® with Sensor Fusion and Tracking Toolbox™. In the context of autonomous driving, the example illustrates how to build a decentralized tracking architecture using a Track-To-Track Fuser block. In the example, each vehicle performs tracking independently as well as fuses tracking information received from other vehicles. This example closely follows the Track-to-Track Fusion for Automotive Safety Applications MATLAB® example.

• Open Model

Ports

Input

Tracks — Track list

Simulink bus containing MATLAB^® structure

Track list, specified as a Simulink bus containing a MATLAB structure. The structure has the form:

Field	Description
NumTracks	Number of tracks
Tracks	Array of track structures

The fields of the track structure are shown in Track Structure.

Prediction Time — Track update time

real scalar

Track update time, specified as a real scalar in seconds. The fuser updates all tracks to this time. The update time must increase with each invocation of the block. The update time must be at least as large as the largest UpdateTime specified in the Tracks input port.

If this port is not enabled, the simulation clock managed by Simulink determines the update time.

Dependencies

To enable this port, on the Port Setting tab, set Prediction time source to Input port.

Source Configurations — Source configuration list

Simulink bus containing MATLAB structure

Source configuration list, specified as a Simulink bus containing a MATLAB structure. The structure has the form:

Field	Description
NumConfigurations	Number of non-default source configurations. The field value must be less than the value specified in the Maximum number of source configurations parameter.
Configurations	Array of source configuration structures.

The fields of the source configuration structure are:

Field Name	Description
SourceIndex	Unique index for the source system, specified as a positive integer.
IsInternalSource	Indicate if the source is internal to the fuser, specified as true or false. An internal source is a source that the fuser directly fuses tracks from even if the tracks are not self reported. For example, if the fuser is at the vehicle level, a tracking radar installed on the associated vehicle is considered internal, while another vehicle that reports fused tracks is considered external.
IsInitializingCentralTracks	Indicate if the source can initialize a central track in the fuser, specified as true or false. A central track is a track maintained in the fuser.
LocalToCentralTransformFcn	Function to transform a track from local to central state space, specified as a string or character vector containing the name of the transform function.
CentralToLocalTransformFcn	Function to transform a track from central to local state space, specified as a string or character vector containing the name of the transform function.

Dependencies

To enable this port, on the Fuser Management tab, select the Update source configurations with time parameter.

State Parameters — Track state parameters

Simulink bus containing MATLAB structure

Track state parameters, specified as a Simulink bus containing a MATLAB structure. The structure has the form:

Field	Description
NumParameters	Number of non-default state parameters, specified as a nonnegative integer
Parameters	Array of state parameter structures

The block uses the value of the Parameters field for the StateParameters field of the generated tracks. You can use these parameters to define the reference frame in which the track is reported or other desirable attributes of the generated tracks.

For example, you can use the following structure to define a rectangular reference frame whose origin position is at [10 10 0] meters and whose origin velocity is [2 -2 0] meters per second with respect to the scenario frame.

Field Name	Value
Frame	"Rectangular"
Position	[10 10 0]
Velocity	[2 -2 0]

Dependencies

To enable this port, in the Tracker Configuration tab, select the Update track state parameters with time parameter.

Output

Confirmed Tracks — Confirmed tracks

Simulink bus containing MATLAB structure

Confirmed tracks, returned as a Simulink bus containing a MATLAB structure. The structure has the form:

Field	Description
NumTracks	Number of tracks.
Tracks	Array of track structures of a length set by the Maximum number of central tracks parameter. Only the first NumTracks of these are actual tracks.

The fields of the track structure are shown in Track Structure.

A track is confirmed if it satisfies the threshold specified in the Confirmation threshold parameter on the Tracks tab.

Tentative Tracks — Tentative tracks

Simulink bus containing MATLAB structure

Tentative tracks, returned as a Simulink bus containing a MATLAB structure. A track is tentative before it is confirmed.

The structure has the form:

Field	Description
NumTracks	Number of tracks.
Tracks	Array of track structures of a length set by the Maximum number of central tracks parameter. Only the first NumTracks of these are actual tracks.

The fields of the track structure are shown in Track Structure.

Dependencies

To enable this port, on the Port Setting tab, select Enable tentative tracks output.

All Tracks — Confirmed and tentative tracks

Simulink bus containing MATLAB structure

Combined list of confirmed and tentative tracks, returned as a Simulink bus containing a MATLAB structure.

The structure has the form:

Field	Description
NumTracks	Number of tracks.
Tracks	Array of track structures of a length set by the Maximum number of central tracks parameter. Only the first NumTracks of these are actual tracks.

The fields of the track structure are shown in Track Structure.

Dependencies

To enable this port, on the Port Setting tab, select Enable all tracks output.

Info — Additional information for analyzing track updates

Simulink bus containing MATLAB structure

Additional information for analyzing track updates, returned as a Simulink bus containing a MATLAB structure.

This table shows the fields of the info structure:

Field	Description
BranchIDsAtStepBeginning	Branch IDs when the update began.
CostMatrix	Cost of assignment matrix.
Assignments	Assignments returned from the assignTOMHT function.
UnassignedTracks	IDs of unassigned branches returned from the tracker.
UnassignedDetections	IDs of unassigned detections returned from the tracker.
InitialBranchHistory	Branch history after branching and before pruning.
InitialBranchScores	Branch scores before pruning.
KeptBranchHistory	Branch history after initial pruning.
KeptBranchScores	Branch scores after initial pruning.
Clusters	Logical array mapping branches to clusters. Branches belong in the same cluster if they share detections in their history or belong to the same track either directly or through other branches.
TrackIncompatibility	Branch incompatibility matrix. The (i,j) element is true if the i-th and j-th branches have shared detections in their history or belong to the same track.
GlobalHypotheses	Logical matrix mapping branches to global hypotheses. Compatible branches can belong in the same hypotheses.
GlobalHypScores	Total score of global hypotheses.
PrunedBranches	Logical array of branches that the pruneTrackBranches function determines to prune.
GlobalBranchProbabilities	Global probability of each branch existing in the global hypotheses.
BranchesDeletedByPruning	Branches deleted by the tracker.
BranchIDsAtStepEnd	Branch IDs when the update ended.

Dependencies

To enable this port, on the Port Setting tab, select Enable information output.

Parameters

Fuser Management

Fuser Index — Unique index for track fuser

1 (default) | positive integer

Unique index for the fuser, specified as a positive integer. Use this property to distinguish different fusers in a multiple-fuser environment.

Example: 2

Assignment algorithm name — Assignment algorithm

MatchPairs (default) | Munkres | Jonker-Volgenant | Auction | Custom

Assignment algorithm, specified as MatchPairs, Munkres, Jonker-Volgenant, Auction, or Custom. Munkres is the only assignment algorithm that guarantees an optimal solution, but it is also the slowest, especially for large numbers of detections and tracks. The other algorithms do not guarantee an optimal solution but can be faster for problems with 20 or more tracks and detections. Use Custom to define your own assignment function and specify its name in the Name of 'Custom' assignment function parameter.

Data Types: char

Name of 'Custom' assignment function — Name of 'Custom' assignment function

function name

Name of 'Custom' assignment function, specified as a function name. An assignment function must have the following syntax:

 [assignments,unassignedCentral,unassignedLocal] = myfun(cost,costNonAssignment)

For an example of an assignment function and a description of its arguments, see assignmunkres.

Example: myfun

Dependencies

To enable this property, set the Assignment algorithm name parameter to Custom.

Threshold for assigning source to central tracks — Threshold for assigning source to central tracks

[1 Inf]*30.0 (default) | positive scalar | 1-by-2 vector of positive values

Threshold for assigning source to central tracks, specified as a positive scalar or a 1-by-2 vector of form [C₁ C₂], where C₁ ≤ C₂. If specified as a scalar, the specified value, val, is expanded to [val Inf].

Initially, the fuser executes a coarse estimation for the normalized distance between all the source and central tracks. The fuser only calculates the accurate normalized distance for the source and central combinations whose coarse normalized distance is less than C₂. Also, the fuser can only assign a local track to a central track if their accurate normalized distance is less than C₁. See Algorithms for an explanation of the normalized distance.

Tip

• Increase the value of C₂ if there are combinations of source and central tracks that should be calculated for assignment but are not. Decrease it if the calculation takes too much time.

• Increase the value of C₁ if there are source tracks that should be assigned to central tracks but are not. Decrease it if there are local tracks that are assigned to central tracks they should not be assigned to (too far away).

Maximum number of central tracks — Maximum number of central tracks

100 (default) | positive integer

Maximum number of central tracks that the tracker can maintain, specified as a positive integer.

Maximum number of source configurations — Maximum number of source configurations

20 (default) | positive integer

Maximum number of source configurations that the fuser can maintain, specified as a positive integer.

Source configurations — Configuration of source systems

struct('SourceIndex',1) (default) | array of source configuration structures

Configuration of source systems, specified as an array of source configuration structures. The fields of a source configuration structure are:

Field Name	Description
SourceIndex	Unique index for the source system, specified as a positive integer.
IsInternalSource	Indicate if the source is internal to the fuser, specified as true or false. An internal source is a source that the fuser directly fuses tracks from even if the tracks are not self reported. For example, if the fuser is at the vehicle level, a tracking radar installed on the associated vehicle is considered internal, while another vehicle that reports fused tracks is considered external.
IsInitializingCentralTracks	Indicate if the source can initialize a central track in the fuser, specified as true or false. A central track is a track maintained in the fuser.
LocalToCentralTransformFcn	Function to transform a track from local to central state space, specified as a string or character vector containing the name of the transform function.
CentralToLocalTransformFcn	Function to transform a track from central to local state space, specified as a string or character vector containing the name of the transform function.

Update source configurations with time — Update source configurations with time

off (default) | on

Select this parameter to enable the input of source configurations through the Source configurations input port.

Track state parameters — Parameters of track state reference frame

structure | structure array

Specify the parameters of the track state reference frame as a structure or a structure array. The block passes the value of this parameter to the StateParameters field of the generated tracks. You can use these parameters to define the reference frame in which the track is reported or other desirable attributes of the generated tracks.

For example, you can use the following structure to define a rectangular reference frame whose origin position is at [10 10 0] meters and whose origin velocity is [2 -2 0] meters per second with respect to the scenario frame.

Field Name	Value
Frame	"Rectangular"
Position	[10 10 0]
Velocity	[2 -2 0]

You can update the track state parameters through the State Parameters input port by selecting the Update track state parameters with time parameter.

Data Types: struct

Update track state parameters with time — Update track state parameters with time

off (default) | on

Select this parameter to enable the input port for track state parameters through the State Parameters input port.

Simulate using — Type of simulation to run

Interpreted execution (default) | Code Generation

Select a simulation type from these options:

• 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 code. The first time you run a simulation, Simulink generates 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.

Tracks

Confirmation threshold [M N] — Threshold for central track confirmation

[2 3] (default) | positive integer | real-valued 1-by-2 vector of positive integers

Threshold for central track confirmation, specified as a positive integer, M, or a real-valued 1-by-2 vector of positive integers, [M N]. A central track is confirmed if it is assigned to local tracks at least M times in the last N updates. If specified as a positive integer, M, the confirmation threshold is expanded to [M M].

Deletion threshold [P Q] — Threshold for central track deletion

[5 5] (default) | positive integer | real-valued 1-by-2 vector of positive integers

Threshold for central track deletion, specified as a positive integer, P, or a 1-by-2 vector of positive integers [P Q] with P ≤ Q. A central track is deleted if the track is not assigned to local tracks at least P times in the last Q updates. If specified a positive integer P, the confirmation threshold is expanded to [P P].

Central track state size — Central track state size

6 (default) | positive integer

Central track state size, specified as a positive integer.

Central track object attributes — Central track object attributes

struct (default) | structure

Central track object attributes, specified as a structure. The tracker passes the value of this parameter to the ObjectAttributes field of the track output.

State transition function — State transition function

constvel (default) | function name

State transition function, specified as a function name. This function calculates the state at time step k based on the state at time step k–1.

• If the Enable additive process noise parameter on the Tracks tab is enabled, the function must use the following syntax:

  x(k) = f(x(k-1),dt)
  

  where:

  • x(k) — The estimated state at time k, specified as a vector or a matrix. If specified as a matrix, then each column of the matrix represents one state vector.

  • dt — The time step for prediction.

• If the Enable additive process noise parameter on the Tracks tab is not enabled, the function must use this syntax:

  x(k) = f(x(k-1),w(k-1),dt)

  where:

  • x(k) — The estimated state at time k, specified as a vector or a matrix. If specified as a matrix, then each column of the matrix represents one state vector.

  • w(k) — The process noise at time k.

  • dt — The time step for prediction.

Example: @constacc

State transition Jacobian function — State transition Jacobian function

function name

Jacobian of the state transition function, specified as a function name. If not specified, the Jacobian is numerically computed, which may increase processing time and numerical inaccuracy. If specified, the function must support one of these two syntaxes:

• If the Enable additive process noise parameter on the Tracks tab is enabled, the function must use this syntax:

  Jx(k) = statejacobianfcn(x(k),dt)
  

  where:

  • x(k) — The estimated state at time k, specified as an M-by-1 vector of real values.

  • dt — The time step for prediction.

  • Jx(k) — The Jacobian of the state transition function with respect to the state, df/dx, evaluated at x(k). The Jacobian is returned as an M-by-M matrix.

• If the Enable additive process noise parameter on the Tracks tab is not enabled, the function must use this syntax::

  [Jx(k),Jw(k)] = statejacobianfcn(x(k),w(k),dt)
  

  where:

  • x(k) — The (estimated) state at time k, specified as an M-by-1 vector of real values.

  • w(k) — The process noise at time k, specified as a W-by-1 vector of real values.

  • dt — The time step for prediction.

  • Jx(k) — The Jacobian of the state transition function with respect to the state, df/dx, evaluated at x(k). The Jacobian is returned as an M-by-M matrix.

  • Jw(k) — The Jacobian of the state transition function with respect to the process noise, df/dw, evaluated at x(k) and w(k). The Jacobian is returned as an M-by-W matrix.

Example: @constaccjac

Process noise matrix — Process noise matrix

eye(3) (default) | positive real scalar | positive definite matrix

Process noise covariance matrix, specified as a positive real scalar or a positive definite matrix.

• When the Enable additive process noise parameter on the Tracks tab is enabled, specify the process noise covariance as a positive real scalar or a positive definite M-by-M matrix. M is the dimension of the state vector. When specified as a scalar, the matrix is an M-by-M diagonal matrix with each diagonal element equal to the scalar.

• When the Enable additive process noise parameter on the Tracks tab is not enabled, specify the process noise covariance as a W-by-W matrix. W is the dimension of the process noise vector.

Example: [1.0 0.05; 0.05 2]

Enable additive process noise — Enable additive process noise

off (default) | on

Enable additive process noise, specified as on or off. When it is on, process noise is added to the state vector. Otherwise, noise is incorporated into the state transition function.

Fusion

State fusion function — State fusion function

Cross (default) | Intersection | Custom

State fusion function, specified as one of those options:

• Cross — Uses the cross-covariance fusion algorithm

• Intersection — Uses the covariance intersection fusion algorithm

• Custom — Enables you to specify a customized fusion function using the Name of 'Custom' fusion function parameter

Use the State fusion parameters source parameter to specify additional parameters used by the state fusion algorithm.

Name of 'Custom' fusion function — Name of custom assignment function

function name

Name of custom assignment function, specified as a string or function name.

The state fusion function must support one of the following syntaxes:

[fusedState,fusedCov] = f(trackState,trackCov)
[fusedState,fusedCov] = f(trackState,trackCov,fuseParams)

where:

• trackState is specified as an N-by-M matrix. N is the dimension of the track state, and M is the number of tracks.

• trackCov is specified as an N-by-N-by-M matrix. N is the dimension of the track state, and M is the number of tracks.

• fuseParams is the optional parameters defined in the State fusion parameters source parameter.

• fusedState is returned as an N-by-1 vector.

• fusedCov is returned as an N-by-N matrix.

Dependencies

To enable this property, set the State fusion function parameter to Custom.

State fusion parameters source — State fusion parameters source

Auto (default) | Property

State fusion parameters source, specified as one of these options:

• Auto — The block uses the default value fusion parameters for each sate fusion algorithm. See Cross covariance factor, Optimize covariance based on, and State fusion custom algorithm parameters for more details.

• Property — Set state fusion parameters using

  • Cross covariance factor parameter when State fusion function is selected as Cross.

  • Optimize covariance based on parameter when State fusion function is selected as Intersection.

  • State fusion custom algorithm parameters parameter when State fusion function is selected as Custom.

Cross covariance factor — Cross covariance factor

0.4 (default) | scalar in range (0,1)

Cross covariance factor, specified as a scalar in the range (0,1). See fusexcov for more details.

Optimize covariance based on — Intersection algorithm criteria

det (default) | trace

Intersection algorithm criteria, specified as det or trace. See fusecovint for more details.

State fusion custom algorithm parameters — State fusion custom algorithm parameters

MATLAB variable

State fusion custom algorithm parameters, specified in any variable type, as long as it matches the setup of the optional fuseParams input of the custom state fusion function, specified in the Name of 'Custom' assignment function parameter.

Fuse only confirmed source tracks — Fuse only confirmed source tracks

on (default) | off

Fuse only confirmed source tracks, specified as on or off. Set this parameter to off if you want to fuse all source tracks regardless of their confirmation status.

Fuse coasted source tracks — Fuse only confirmed source tracks

off (default) | on

Fuse coasted source tracks, specified as off or on. Set this parameter to on if you want to fuse coasted source tracks. Set it to off if you want to only fuse source tracks that are not coasted.

Port Setting

Prediction time source — Source of prediction time

Auto (default) | Input port

Source for prediction time, specified as Input port or Auto. Select Input port to input an update time by using the Prediction Time input port. Otherwise, the simulation clock managed by Simulink determines the update time.

Enable tentative tracks output — Enable output port for tentative tracks

off (default) | on

Select this parameter to enable the output of tentative tracks through the Tentative Tracks output port.

Enable all tracks output — Enable output port for all tracks

off (default) | on

Select this parameter to enable the output of all the tracks through the All Tracks output port.

Enable information output — Enable output port for analysis information

off (default) | on

Select this parameter to enable the output port for analysis information through the Info output port.

Source of output bus name — Source of output track bus name

Auto (default) | Property

Source of the output track bus name, specified as:

• Auto — The block automatically creates an output track bus name.

• Property — Specify the output track bus name by using the Specify an output bus name parameter.

Source of output info bus name — Source of output info bus name

Auto (default) | Property

Source of the output info bus name, specified as one of these options:

• Auto — The block automatically creates an output info bus name.

• Property — Specify the output info bus name by using the Fuser info bus name parameter.

Algorithms

Track Structure

The fields of the track structure are:

Field	Definition
SourceIndex	Unique source index used to distinguish tracking sources in a multiple tracker environment.
TrackID	Unique track identifier used to distinguish multiple tracks.
BranchID	Unique track branch identifier used to distinguish multiple track branches.
UpdateTime	Time at which the track is updated. Units are in seconds.
Age	Number of times the track survived.
State	Value of the state vector at the update time.
StateCovariance	Uncertainty covariance matrix.
TrackLogic	Confirmation and deletion logic type, returned as 'History' or 'Score'.
TrackLogicState	The current state of the track logic type. Based on the logic type TrackLogic, the logic state is returned as: 'History' — A 1-by-K logical array, where K is the number of latest track logical states recorded. In the array, 1 denotes hit and 0 denote miss. 'Score' — A 1-by-2 array of real scalars, [cs ms]. cs is the current score and ms is the maximum score.
IsConfirmed	Confirmation status. This field is true if the track is confirmed to be a real target.
IsCoasted	Coasting status. This field is true if the track is updated without a new detection.
IsSelfReported	Indicate if the track is reported by the tracker. This field is used in a track fusion environment. It is returned as true by default.
ObjectClassID	Integer value representing the object classification. The value 0 represents an unknown classification. Nonzero classifications apply only to confirmed tracks.
ObjectAttributes	Additional information of the track.

Extended Capabilities

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

Version History

Introduced in R2021a

R2023a: Simulink buses do not show in workspace

As of R2023a, the Simulink buses created by this block no longer show in MATLAB workspace.