TSOA Position Estimator

Estimate target position from time-sum of arrival

Since R2025a

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  • Time sum-of-arrival position estimator

Libraries:
Phased Array System Toolbox / Direction of Arrival

Description

Estimate target position from time-sum-of-arrival (TSOA) measurements and anchor positions. The block also estimates the variance of the time-sum of arrival measurements.

Ports

Input

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Time-sum of arrival estimates, input as a real-valued J-by-L-by-K array, where J is the number of transmitting anchors, L is the number of receiving anchors, and K is the number of TSOA groups. Each page represents a TSOA group corresponding to the TSOAs measured at the JL anchor pairs for a potential target. In each page, the element in the jth row and lth column of TSOAEst represents the estimated TSOA from the jth transmit anchor to the lth receive anchor. When the actual values of TSOAVar are unknown, TSOAVar is typically chosen to be a matrix with each element chosen to be the same real positive value. This value does not impact affect the solution tgtposest.Units are in seconds.

Data Types: single | double

TSOA estimation variance, input as a real-valued J-by-L matrix or real-valued J-by-L-by-K array. Representing the variance of TSOA estimation variance for the JL anchor pairs. When TSOAVsr is a matrix, the variance estimates for JL anchor pairs are the same for all K TSOA groups. When TSOAVar is an array, the variance estimates for JL anchor pairs are different for different TSOA groups. Units are in seconds-squared.

Data Types: single | double

Transmitting anchor positions, input as a real-valued Q-by-J matrix. J is the number of transmitting anchors. Each column represents the position of a different anchor. Positions may be two or three dimensional. For two dimensional positions, Q=2 and for three dimensional positions, Q=3. The jth column of txpos denotes the position of the jth transmitter in Q-dimensional Cartesian space. Units are in meters.

Example: [20 31 –16; 13 64 –44]

Data Types: single | double

Receiving anchor positions, input as a real-valued Q-by-L matrix. L is the number of receiving anchors. Each column represents the position of a different anchor. Positions may be two or three dimensional. For two dimensional positions, Q=2 and for three dimensional positions, Q=3. The lth column of rxpos denotes the position of the lth receiver in Q-dimensional Cartesian space. Units are in meters.

Example: [20 31 –16; 13 64 –44]

Data Types: single | double

Output

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Estimated target positions, returned as a Q-by-1 vector representing the estimated target position obtained from TSOA measurements. Units are in meters.

Data Types: single | double

Target position covariance matrix, returned as a real-valued positive semi-definite Q-by-Q matrix. The covariance matrix represents the estimated target position covariance calculated from the Cramer-Rao lower bound (CRLB) of the TSOA position estimator. Calculating the covariance requires the knowledge of TSOAVar. When TSOAVar is inaccurate, TgtPosCov is also inaccurate. When TSOAVar is accurate and small, the TgtPosCov value represents the TSOA position estimate CRLB. Units are in meters-squared.

Dependencies

To enable this output port, select the Output covariance of TSOA position estimate check box.

Data Types: single | double

Parameters

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To edit block parameters interactively, use the Property Inspector. From the Simulink® Toolstrip, on the Simulation tab, in the Prepare gallery, select Property Inspector.

Signal propagation speed, specified as a positive real scalar. Units are in meters per second.

Example: 3e8

Data Types: double

Select the Output covariances of TSOA position estimates check box to enable the TgtPosCov output port containing the TSOA position covariances. Units are meters-squared.

Data Types: Boolean

Block simulation, specified as Interpreted Execution or Code Generation. If you want your block to use the MATLAB® interpreter, choose Interpreted Execution. If you want your block to run as compiled code, choose Code Generation. Compiled code requires time to compile but usually runs faster.

Interpreted execution is useful when you are developing and tuning a model. The block runs the underlying System object™ in MATLAB. You can change and execute your model quickly. When you are satisfied with your results, you can then run the block using Code Generation. Long simulations run faster with generated code than in interpreted execution. You can run repeated executions without recompiling, but if you change any block parameters, then the block automatically recompiles before execution.

This table shows how the Simulate using parameter affects the overall simulation behavior.

When the Simulink model is in Accelerator mode, the block mode specified using Simulate using overrides the simulation mode.

Acceleration Modes

Block SimulationSimulation Behavior
NormalAcceleratorRapid Accelerator
Interpreted ExecutionThe block executes using the MATLAB interpreter.The block executes using the MATLAB interpreter.Creates a standalone executable from the model.
Code GenerationThe block is compiled.All blocks in the model are compiled.

For more information, see Choosing a Simulation Mode (Simulink).

Programmatic Use

Block Parameter: SimulateUsing
Type: enum
Values: Interpreted Execution, Code Generation
Default: Interpreted Execution

Extended Capabilities

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

Version History

Introduced in R2025a