DOA定位算法源码程序 - matlab算法设计

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标题：DOA定位算法源码程序
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所属分类: 算法设计资源类型：文件大小: 1.36 KB 上传时间: 2016-01-30 12:27:53 下载次数: 91 资源积分：1分提供者: 源码共享 DOA定位算法源码程序

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DOA定位算法源码程序，程序员在编程的过程中可以参考学习使用，希望对IT程序员有用，此源码程序简单易懂、方便阅读，有很好的学习价值！

% Simulation of MUSIC, ESPRIT, MVDR, Min-Norm and Classical DOA

% algorithms for a uniform linear array.

clear all;

clc ;

doas=[-30 -5 40 70]*pi/180; %DOA抯 of signals in rad.

P=[1 1 1 1]; %Power of incoming signals

N=10; %Number of array elements

K=1024; %Number of data snapshots

d=0.5; %Distance between elements in wavelengths

noise_var=1; %Variance of noise

r=length(doas); %Total number of signals

% Steering vector matrix. Columns will contain the steering vectors

% of the r signals

A=exp(-i*2*pi*d*(0:N-1)'*sin([doas(:).']));

% Signal and noise generation

sig=round(rand(r,K))*2-1; % Generate random BPSK symbols for each of the

% r signals

noise=sqrt(noise_var/2)*(randn(N,K)+i*randn(N,K)); %Uncorrelated noise

X=A*diag(sqrt(P))*sig+noise; %Generate data matrix

R=X*X'/K; %Spatial covariance matrix

[Q ,D]=eig(R); %Compute eigendecomposition of covariance matrix

[D,I]=sort(diag(D),1,'descend'); %Find r largest eigenvalues

Q=Q (:,I); %Sort the eigenvectors to put signal eigenvectors first

Qs=Q (:,1:r); %Get the signal eigenvectors

Qn=Q(:,r+1:N); %Get the noise eigenvectors

% MUSIC algorithm

% Define angles at which MUSIC 搒pectrum?will be computed

angles=(-90:0.1:90);

%Compute steering vectors corresponding values in angles

a1=exp(-i*2*pi*d*(0:N-1)'*sin([angles(:).']*pi/180));

for k=1:length(angles)

%Compute MUSIC 搒pectrum?

music_spectrum(k)=(a1(:,k)'*a1(:,k))/(a1(:,k)'*Qn*Qn'*a1(:,k));

end

figure(1)

plot(angles,abs(music_spectrum))

title('MUSIC Spectrum')

xlabel('Angle in degrees')

%ESPRIT Algorithm

phi= linsolve(Qs(1:N-1,:),Qs(2:N,:));

ESPRIT_doas=asin(-angle(eig(phi))/(2*pi*d))*180/pi;

%MVDR

IR=inv(R); %Inverse of covariance matrix

for k=1:length(angles)

mvdr(k)=1/(a1(:,k)'*IR*a1(:,k));

end

figure(gcf+1)

plot(angles,abs(mvdr))

xlabel('Angle in degrees')

title('MVDR')

%Min norm method

alpha=Qs(1,:);

Shat=Qs(2:N,:);

ghat=-Shat*alpha'/(1-alpha*alpha');

g=[1;ghat];

for k=1:length(angles)

minnorm_spectrum(k)=1/(abs(a1(:,k)'*g));

end

figure(gcf+1)

plot(angles,abs(minnorm_spectrum))

xlabel('Angle in degrees')

title('Min-Norm')

%Estimate DOA抯 using the classical beamformer

for k=1:length(angles)

Classical(k)=(a1(:,k)'*R*a1(:,k));

end

figure(gcf+1)

plot(angles,abs(Classical))

xlabel('Angle in degrees')

title('Classical Beamformer')

文件列表（点击上边下载按钮，如果是垃圾文件请在下面评价差评或者投诉）:

DOA定位算法源码程序/
DOA定位算法源码程序/DOA.m

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