Documentation

This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

step

System object: phased.MVDRBeamformer
Package: phased

Perform MVDR beamforming

Syntax

Y = step(H,X)
Y = step(H,X,XT)
Y = step(H,X,ANG)
Y = step(H,X,XT,ANG)
[Y,W] = step(___)

Description

    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.

Y = step(H,X) performs MVDR beamforming on the input, X, and returns the beamformed output in Y. This syntax uses X as the training samples to calculate the beamforming weights.

Y = step(H,X,XT) uses XT as the training samples to calculate the beamforming weights. This syntax is available when you set the TrainingInputPort property to true.

Y = step(H,X,ANG) uses ANG as the beamforming direction. This syntax is available when you set the DirectionSource property to 'Input port'.

Y = step(H,X,XT,ANG) combines all input arguments. This syntax is available when you set the TrainingInputPort property to true and set the DirectionSource property to 'Input port'.

[Y,W] = step(___) returns the beamforming weights, W. This syntax is available when you set the WeightsOutputPort property to true.

    Note:   The object performs an initialization the first time the step method is executed. This initialization locks nontunable properties (MATLAB) and input specifications, such as dimensions, complexity, and data type of the input data. If you change a nontunable property or an input specification, the System object issues an error. To change nontunable properties or inputs, you must first call the release method to unlock the object.

Input Arguments

H

Beamformer object.

X

Input signal, specified as an M-by-N matrix. If the sensor array contains subarrays, N is the number of subarrays; otherwise, N is the number of elements. If you set the TrainingInputPort to false, M must be larger than N; otherwise, M can be any positive integer.

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.

XT

Training samples, specified as a P-by-N matrix. If the sensor array contains subarrays, N is the number of subarrays; otherwise, N is the number of elements. P must be larger than N.

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.

ANG

Beamforming directions, specified as a two-row matrix. Each column has the form [AzimuthAngle; ElevationAngle], in degrees. Each azimuth angle must be between –180 and 180 degrees, and each elevation angle must be between –90 and 90 degrees.

Output Arguments

Y

Beamformed output. Y is an M-by-L matrix, where M is the number of rows of X and L is the number of beamforming directions.

W

Beamforming weights. W is an N-by-L matrix, where L is the number of beamforming directions. If the sensor array contains subarrays, N is the number of subarrays; otherwise, N is the number of elements.

Examples

expand all

Apply an MVDR beamformer to a 5-element ULA. The incident angle of the signal is 45 degrees in azimuth and 0 degree in elevation. The signal frequency is .01 hertz. The carrier frequency is 300 MHz.

t = [0:.1:200]';
fr = .01;
xm = sin(2*pi*fr*t);
c = physconst('LightSpeed');
fc = 300e6;
rng('default');
incidentAngle = [45;0];
array = phased.ULA('NumElements',5,'ElementSpacing',0.5);
x = collectPlaneWave(array,xm,incidentAngle,fc,c);
noise = 0.1*(randn(size(x)) + 1j*randn(size(x)));
rx = x + noise;

Compute the beamforming weights

beamformer = phased.MVDRBeamformer('SensorArray',array,...
    'PropagationSpeed',c,'OperatingFrequency',fc,...
    'Direction',incidentAngle,'WeightsOutputPort',true);
[y,w] = beamformer(rx);

Plot the signals

plot(t,real(rx(:,3)),'r:',t,real(y))
xlabel('Time')
ylabel('Amplitude')
legend('Original','Beamformed')

Plot the array response pattern using the MVDR weights

pattern(array,fc,[-180:180],0,'PropagationSpeed',c,...
    'Weights',w,'CoordinateSystem','rectangular',...
    'Type','powerdb');

Was this topic helpful?