phased.MVDREstimator2D

2-D MVDR (Capon) spatial spectrum estimator

Description

The MVDREstimator2D object computes a 2-D minimum variance distortionless response (MVDR) spatial spectrum estimate. This DOA estimator is also referred to as a Capon estimator.

To estimate the spatial spectrum:

1. Define and set up your 2-D MVDR spatial spectrum estimator. See Construction.

2. Call step to estimate the spatial spectrum according to the properties of phased.MVDREstimator2D. 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.MVDREstimator2D creates a 2-D MVDR spatial spectrum estimator System object, H. The object estimates the signal’s spatial spectrum using a narrowband MVDR beamformer.

H = phased.MVDREstimator2D(Name,Value) creates 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	Handle to sensor array Specify the sensor array as a handle. The sensor array must be an array object in the phased package. The array cannot 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
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
ForwardBackwardAveraging	Perform forward-backward averaging Set this property to true to use forward-backward averaging to estimate the covariance matrix for sensor arrays with conjugate symmetric array manifold. Default: false
AzimuthScanAngles	Azimuth scan angles (degrees) Specify the azimuth scan angles (in degrees) as a real vector. The angles must be between –180 and 180, inclusive. You must specify the angles in ascending order. You can specify this property as single or double precision. Default: -90:90
ElevationScanAngles	Elevation scan angles Specify the elevation scan angles (in degrees) as a real vector or scalar. The angles must be between –90 and 90, inclusive. You must specify the angles in ascending order. You can specify this property as single or double precision. Default: 0
DOAOutputPort	Enable DOA output To obtain the signal's direction of arrival (DOA), set this property to true and use the corresponding output argument when invoking step. If you do not want to obtain the DOA, set this property to false. Default: false
NumSignals	Number of signals Specify the number of signals for DOA estimation as a positive scalar integer. This property applies when you set the DOAOutputPort property to true. You can specify this property as single or double precision. Default: 1

Methods

plotSpectrum	Plot spatial spectrum
reset	Reset states of 2-D MVDR spatial spectrum estimator object
step	Perform spatial spectrum estimation

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

Examples

Estimate DOA of Two Signals Arriving at URA

Estimate the DOAs of two signals received by a 50-element URA with a rectangular lattice. The antenna operating frequency is 150 MHz. The actual direction of the first signal is −37° in azimuth and 0° in elevation. The direction of the second signal is 17° in azimuth and 20° degrees in elevation. Then, plot the spatial spectrum.

Create the arriving signals.

fs = 8000;
t = (0:1/fs:1).';
x1 = cos(2*pi*t*300);
x2 = cos(2*pi*t*400);
array = phased.URA('Size',[5 10],'ElementSpacing',[1 0.6]);
array.Element.FrequencyRange = [100e6 300e6];
fc = 150e6;
x = collectPlaneWave(array,[x1 x2],[-37 0;17 20]',fc);

Add noise.

noise = 0.1*(randn(size(x))+1i*randn(size(x)));

Create the MVDR DOA estimator and estimate the DOAs.

estimator = phased.MVDREstimator2D('SensorArray',array,...
    'OperatingFrequency',fc,...
    'DOAOutputPort',true,'NumSignals',2,...
    'AzimuthScanAngles',-50:50,...
    'ElevationScanAngles',-30:30);
[~,doas] = estimator(x + noise);

Plot the spectrum.

plotSpectrum(estimator)

Algorithms

Data 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] Van Trees, H. Optimum Array Processing. New York: Wiley-Interscience, 2002.

Extended Capabilities

C/C++ Code Generation

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

Usage notes and limitations:

See System Objects in MATLAB Code Generation (MATLAB Coder).

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.

Version History

Introduced in R2011a