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Doppler Estimator

Doppler estimation

  • Library:
  • Phased Array System Toolbox / Detection

Description

The Doppler Estimator block estimates the Doppler (radial speed) of target detections obtained from the radar response data.

Ports

Input

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Doppler-processed response data cube, specified as a complex-valued P-by-1 column vector, a complex-valued M-by-P matrix, or a complex-valued M-by-N-by-P array.M represents the number of range samples, N is the number of sensor elements or beams, and P is the number of Doppler bins.

The size of the first dimension of this input matrix can vary to simulate a changing signal length, such as a pulse waveform with variable pulse repetition frequency.

Data Types: double
Complex Number Support: Yes

Doppler grid values along the Doppler dimension, specified as a real-valued P-by-1 column vector. Doppler defines the Doppler values corresponding to the Doppler dimension of data input to the Resp port. Doppler values must be monotonically increasing and equally spaced. Units are in hertz or meters/sec.

Example: [-0.3,-0.2,-0.1,0,0.1,0.2,0.3]

Data Types: double

Detection indices, specified as a real-valued Nd-by-Q matrix. Q is the number of detections and Nd is the number of dimensions in the response data cube, Resp. Each column of DetIdx contains the indices of a detection in the response data cube.

Noise power at detection locations, specified as a positive scalar or real-valued 1-by-Q row vector positive values. Q is the number of detections specified in the DetIdx input port.

Dependencies

To enable this port, select the Output variance for parameter estimates parameter, and then set Source of noise power parameter to Input port.

Cluster IDs, specified as a real-valued 1-by-Q row vector, where Q is the number of detections specified in the DetIdx input port. Each element of Clusters corresponds to an element of DetIdx.

Dependencies

To enable this input port, select the Enable cluster ID input checkbox.

Output

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Doppler estimates, returned as a real-valued K-by-1 column vector.

  • When Enable cluster ID input is not selected, each Doppler estimate corresponds to one of the columns in the DetIdx input port. Then K equals the number of elements, Q, of DetIdx.

  • When Enable cluster ID input is selected, each Doppler estimate corresponds to one of the cluster IDs in the Clustersinput port. Then K equals the number of unique cluster IDs.

Doppler estimation variance, returned as a positive, real-valued K-by-1 column vector, where K is the dimension of Est. Each element of Var corresponds to an element of Est. The estimator variance is computed using the Ziv-Zakai bound.

Dependencies

To enable this port, select the Output variance for parameter estimates parameter.

Parameters

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The maximum number of estimates to report, specified as a positive integer. When the number of requested estimates is greater than the number elements in DetIdx, the remainder is filled with NaN.

Data Types: double

Enable the Cluster input port to pass in cluster association information.

Data Types: Boolean

Enables the output of the parameter estimate variances via the Var port.

Data Types: Boolean

Number of pulses in Doppler processed waveform, specified as a positive integer.

Dependencies

To enable this parameter, select the Output variance for parameter estimates Output variance for parameter estimates parameter.

Data Types: double

Source of the noise power, specified as Property or Input port. If you set this parameter to Property, use the Noise power parameter to set the noise power at the detection locations. When set the parameter to Input port, specify noise power via the NoisePower input port.

Noise power for detections, specified as a positive scalar. The same noise power value is applied to all detections. Noise power is in linear units.

Dependencies

To enable this parameter, select the Output variance for parameter estimates checkbox and set the Source of noise power parameter to Property.

Data Types: double

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 than in interpreted execution. You can run repeated executions without recompiling. However, if you change any block parameters, then the block automatically recompiles before execution.

When setting this parameter, you must take into account the overall model simulation mode. The table shows how the Simulate using parameter interacts with the overall simulation mode.

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) from the Simulink documentation.

Data Types: char

Introduced in R2017a

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