phased.STAPSMIBeamformer

Sample matrix inversion (SMI) beamformer

Description

The SMIBeamformer object implements a sample matrix inversion space-time adaptive beamformer. The beamformer works on the space-time covariance matrix.

To compute the space-time beamformed signal:

1. Define and set up your SMI beamformer. See Construction.

2. Call step to execute the SMI beamformer algorithm according to the properties of phased.STAPSMIBeamformer. The behavior of step is specific to each object in the toolbox.

Note

Starting in R2016b, instead of using the step method to perform the operation defined by the System object™, you can call the object with arguments, as if it were a function. For example, y = step(obj,x) and y = obj(x) perform equivalent operations.

Construction

H = phased.STAPSMIBeamformer creates a sample matrix inversion (SMI) beamformer System object, H. The object performs the SMI space-time adaptive processing (STAP) on the input data.

H = phased.STAPSMIBeamformer(Name,Value) creates an SMI object, H, with each specified property Name set to the specified Value. You can specify additional name-value pair arguments in any order as (Name1,Value1,...,NameN,ValueN).

Properties

SensorArray	Sensor array Sensor array specified as an array System object belonging to the phased package. A sensor array can contain subarrays. Default: phased.ULA with default property values
PropagationSpeed	Signal propagation speed Specify the propagation speed of the signal, in meters per second, as a positive scalar. You can specify this property as single or double precision. Default: Speed of light
OperatingFrequency	System operating frequency Specify the operating frequency of the system in hertz as a positive scalar. The default value corresponds to 300 MHz. You can specify this property as single or double precision. Default: 3e8
PRFSource	Source of pulse repetition frequency Source of the PRF values for the STAP processor, specified as 'Property' or 'Input port'. When you set this property to 'Property', the PRF is determined by the value of the PRF property. When you set this property to 'Input port', the PRF is determined by an input argument to the step method at execution time. Default: 'Property'
PRF	Pulse repetition frequency Pulse repetition frequency (PRF) of the received signal, specified as a positive scalar. Units are in Hertz. This property can be specified as single or double precision. Dependencies To enable this property, set the PRFSource property to 'Property'. Default: 1
DirectionSource	Source of targeting direction Specify whether the targeting direction for the STAP processor comes from the Direction property of this object or from an input argument in step. Values of this property are: 'Property' The Direction property of this object specifies the targeting direction. 'Input port' An input argument in each invocation of step specifies the targeting direction. Default: 'Property'
Direction	Targeting direction Specify the targeting direction of the SMI processor as a column vector of length 2. The direction is specified in the format of [AzimuthAngle; ElevationAngle] (in degrees). Azimuth angle should be between –180 and 180. Elevation angle should be between –90 and 90. This property applies when you set the DirectionSource property to 'Property'. You can specify this property as single or double precision. Default: [0; 0]
NumPhaseShifterBits	Number of phase shifter quantization bits The number of bits used to quantize the phase shift component of beamformer or steering vector weights. Specify the number of bits as a non-negative integer. A value of zero indicates that no quantization is performed. You can specify this property as single or double precision. Default: 0
DopplerSource	Source of targeting Doppler Specify whether the targeting Doppler for the STAP processor comes from the Doppler property of this object or from an input argument in step. Values of this property are: 'Property' The Doppler property of this object specifies the Doppler. 'Input port' An input argument in each invocation of step specifies the Doppler. Default: 'Property'
Doppler	Targeting Doppler frequency Specify the targeting Doppler of the STAP processor as a scalar. This property applies when you set the DopplerSource property to 'Property'. You can specify this property as single or double precision. Default: 0
NumGuardCells	Number of guarding cells Specify the number of guard cells used in the training as an even integer. This property specifies the total number of cells on both sides of the cell under test. You can specify this property as single or double precision. Default: 2, indicating that there is one guard cell at both the front and back of the cell under test
NumTrainingCells	Number of training cells Specify the number of training cells used in the training as an even integer. Whenever possible, the training cells are equally divided before and after the cell under test. You can specify this property as single or double precision. Default: 2, indicating that there is one training cell at both the front and back of the cell under test
WeightsOutputPort	Output processing weights To obtain the weights used in the STAP processor, set this property to true and use the corresponding output argument when invoking step. If you do not want to obtain the weights, set this property to false. Default: false

Methods

step	Perform SMI STAP processing on input data

Common to All System Objects
release	Allow System object property value changes

Examples

Process Data Cube Using SMI

Process a data cube using an SMI beamformer. The weights are calculated for the 71st cell of a collected data cube pointing in the azimuth and elevation direction (45°,-35°) and with a Doppler of 12.980 kHz.

Load the cube data and create the SMI beamformer.

load STAPExampleData;
beamformer = phased.STAPSMIBeamformer('SensorArray',STAPEx_HArray, ...
    'PRF',STAPEx_PRF,'PropagationSpeed',STAPEx_PropagationSpeed, ...
    'OperatingFrequency',STAPEx_OperatingFrequency, ...
    'NumTrainingCells',100,'WeightsOutputPort',true, ...
    'DirectionSource','Input port','DopplerSource','Input port');
[y,w] = beamformer(STAPEx_ReceivePulse,71,[45;-35],12.980e3);

Plot the angle-doppler response.

response = phased.AngleDopplerResponse( ...
    'SensorArray',beamformer.SensorArray, ...
    'OperatingFrequency',beamformer.OperatingFrequency, ...
    'PRF',beamformer.PRF,'PropagationSpeed',beamformer.PropagationSpeed);
plotResponse(response,w)

Algorithms

Weight Computation

The optimum beamformer weights are

$$w=k{R}^{-1}v$$

where:

• k is a scalar

• R represents the space-time covariance matrix

• v indicates the space-time steering vector

Because the space-time covariance matrix is unknown, you must estimate that matrix from the data. The sample matrix inversion (SMI) algorithm estimates the covariance matrix by designating a number of range gates to be training cells. Because you use the training cells to estimate the interference covariance, these cells should not contain target returns. To prevent target returns from contaminating the estimate of the interference covariance, you can specify insertion of a number of guard cells before and after the designated target cell.

To use the general algorithm for estimating the space-time covariance matrix:

1. Assume you have a M-by-N-by-K matrix. M represents the number of slow-time samples, and N is the number of array sensors. K is the number of training cells (range gates for training). Also assume that the number of training cells is an even integer and that you can designate K/2 training cells before and after the target range gate excluding the guard cells. Reshape the M-by-N-by-K matrix into a MN-by-K matrix by letting X denote the MN-by-K matrix.

2. Estimate the space-time covariance matrix as

   $$\frac{1}{K}X{X}^H$$

3. Invert the space-time covariance matrix estimate.

4. Obtain the beamforming weights by multiplying the sample space-time covariance matrix inverse by the space-time steering vector.

Single Precision

This System object supports single and double precision for input data, properties, and arguments. If the input data X is single precision, the output data is single precision. If the input data X is double precision, the output data is double precision. The precision of the output is independent of the precision of the properties and other arguments.

References

[1] Guerci, J. R. Space-Time Adaptive Processing for Radar. Boston: Artech House, 2003.

[2] Ward, J. “Space-Time Adaptive Processing for Airborne Radar Data Systems,” Technical Report 1015, MIT Lincoln Laboratory, December, 1994.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

Version History

Introduced in R2011a