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Range Response

Range response

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  • Range Response block

Libraries:
Phased Array System Toolbox / Detection

Description

The Range Response block performs range filtering on fast-time (range) data, using either a matched filter or an FFT-based algorithm. The output is typically used as input to a detector. Matched filtering improves the SNR of pulsed waveforms. For continuous FM signals, FFT processing extracts the beat frequency of FMCW waveforms. Beat frequency is directly related to range.

The input to the block is a radar data cube. The organization of the data cube follows the Phased Array System Toolbox™ convention. The first dimension of the cube represents the fast time samples or ranges of the received signals. The second dimension represents multiple spatial channels such as different sensors or beams. The third dimension, slow time, represent pulses. Range filtering operates along the fast-time dimension of the cube. Processing along the other dimensions is not performed. If the data contains only one channel or pulse, the data cube can contain fewer than three dimensions. Because this object performs no Doppler processing, you can use it to process noncoherent radar pulses.

The output of the block is also a data cube with the same number of dimensions as the input. Its first dimension contains range-processed data but its length can differ from the first dimension of the input data cube.

Ports

Input

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Input data cube, specified as a complex-valued K-by-1 column vector, a complex-valued K-by-L matrix, or a complex-valued K-by-N-by-L array.

  • K is the number of range or time samples.

  • N is the number of independent channels such as sensors or directions.

  • L is the number of pulses or sweeps in the input signal.

See Radar Data Cube Concept.

Each K-element column vector is processed independently.

For an FMCW waveform, with a triangle sweep, the sweeps alternate between positive and negative slopes. However, Range Response is designed to process consecutive sweeps of the same slope. To apply the Range Response block for a triangle-sweep system, use one of the following approaches:

  • Specify a positive Sweep slope parameter value, with X corresponding to upsweeps only. After obtaining the Doppler or speed values, divide them by 2.

  • Specify a negative Sweep slope parameter value, with X corresponding to downsweeps only. After obtaining the Doppler or speed values, divide them by 2.

The size of the first dimension of the input matrix can vary to simulate a changing signal length. A size change can occur, for example, in the case of a pulse waveform with variable pulse repetition frequency.

Data Types: double
Complex Number Support: Yes

Matched filter coefficients, specified as a complex-valued column vector. The length of the vector must be less than or equal to the number of rows in the input data, K.

Dependencies

To enable this port, set Range processing method to Matched filter.

Data Types: double
Complex Number Support: Yes

Reference signal used for dechirping the input signal, specified as a complex-valued K-by-1 column vector. The number of rows must equal the length of the first dimension of X.

Dependencies

To enable this port, set Range processing method to FFT and select the Dechirp input signal parameter.

Data Types: double
Complex Number Support: Yes

Output

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Range response data cube, returned as a

  • Complex-valued M-element column vector

  • Complex-valued M-by-L matrix

  • Complex-valued M-by-N by-L array

See Radar Data Cube Concept. The value of M depends on the type of processing

Range processing methodDechirp input signalValue of M
FFToff

If you set the Source of FFT length in range processing to Auto,M = K, the length of the first dimension of x. Otherwise, M equals the value of the FFT length in range processing parameter.

onM equals the number of rows, K, of the input signal.
Matched filterN/AM equals the number of rows, K, of the input signal.

Data Types: double
Complex Number Support: Yes

Range values along the first dimension of the Resp output data port, specified as a real-valued M-by-1 column vector. This quantity defines the range values along the first dimension of the Resp output port data. Units are in meters.

Data Types: double

Parameters

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Range processing method, specified as Matched filter or FFT.

Matched filterThe block applies a matched filter to the incoming signal. This approach is commonly used for pulsed signals, where the matched filter is the time reverse of the transmitted signal.
FFTThe block applies an FFT to the input signal. This approach is commonly used for FMCW and linear FM pulsed signals.

Data Types: char

Signal propagation speed, specified as a real-valued positive scalar. The default value of the speed of light is the value returned by physconst('LightSpeed').

Data Types: double

Select this parameter to inherit the sample rate from upstream blocks. Otherwise, specify the sample rate using the Sample rate (Hz) parameter.

Data Types: Boolean

Specify the signal sampling rate as a positive scalar. Units are in Hz.

Dependencies

To enable this parameter, clear the Inherit sample rate check box.

Data Types: double

Specify the slope of the linear FM sweep as a scalar. This parameter must match the actual sweep of the input data in port X.

Dependencies

To enable this parameter, set Range processing method to FFT.

Data Types: double

Select this parameter to enable dechirping of input signal.

Dependencies

To enable this parameter, set Range processing method to FFT.

Data Types: Boolean

Source of FFT length for range processing, specified as Auto or Property

AutoThe FFT length equals the number of rows of the input data cube.
PropertySpecify FFT length in the FFT length in range processing parameter.

Dependencies

To enable this parameter, set Range processing method to FFT.

Data Types: char

FFT length for range processing, specified as a positive integer.

Dependencies

To enable this parameter, set Range processing method to FFT and Source of FFT length in range processing to Property.

Data Types: double

Range FFT weighting window, specified as None, Hamming, Chebyshev, Hann, Kaiser, or Taylor.

If you set this property to Taylor, the generated Taylor window has four nearly constant sidelobes next to the mainlobe.

Dependencies

To enable this parameter, set Range processing method to FFT.

Data Types: char

Sidelobe attenuation for range processing, specified as a positive scalar. Units are in dB.

Dependencies

To enable this parameter, set Range processing method to FFT and Range processing window to Kaiser, Chebyshev, or Taylor.

Data Types: double

Set reference range at the center of range grid, specified as on or off. Selecting this check box, enables you to set the reference range at the center of the range grid. Otherwise, the reference range is set to the beginning of the range grid.

Dependencies

To enable this property, set the Range processing method to FFT.

Reference range of the range grid, specified as a nonnegative scalar.

  • If you set the Range processing method parameter to Matched filter, the reference range is set to the start of the range grid.

  • If you set the Range processing method property to FFT, the reference range depends on the Set reference range at center check box.

    • When you select the Set reference range at center check box, the reference range is set to the center of the range grid.

    • If you do not select the Set reference range at center check box, the reference range is set to the start of the range grid.

    Units are in meters.

Example: 1000.0

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 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

References

[1] Richards, M. Fundamentals of Radar Signal Processing, 2nd ed. McGraw-Hill Professional Engineering, 2014.

[2] Richards, M., J. Scheer, and W. Holm, Principles of Modern Radar: Basic Principles. SciTech Publishing, 2010.

Version History

Introduced in R2017a

See Also

Blocks

Functions

Objects