基于压缩感知的二维DOA估计matlab代码
时间: 2023-07-16 14:16:18 浏览: 67
以下是基于压缩感知的二维DOA估计的Matlab代码示例:
```matlab
% 二维DOA估计 - 压缩感知
clc;
clear;
close all;
% 参数设置
M = 8; % 阵元数
N = 64; % 信号长度
K = 4; % 稀疏度
theta = [30, 40]; % 两个信号的DOA角度
SNR = 10; % 信噪比
% 产生二维坐标
x = linspace(-1, 1, M);
y = linspace(-1, 1, M);
[X, Y] = meshgrid(x, y);
pos = [X(:), Y(:)];
% 产生信号
S = zeros(M, N);
A = zeros(M, 2);
for ii = 1:length(theta)
a1 = exp(1j*pi*cosd(theta(ii))*(0:M-1)');
a2 = exp(1j*pi*sind(theta(ii))*(0:M-1)');
A(:,ii) = a1 + a2;
S = S + A(:,ii)*randn(1,N) + 1j*A(:,ii)*randn(1,N);
end
% 添加噪声
noise = randn(M, N) + 1j*randn(M, N);
noise = noise./norm(noise, 'fro');
noise = noise*norm(S, 'fro')/(10^(SNR/20));
X = S + noise;
% 产生随机矩阵
Phi = randn(K, M*N)/sqrt(K);
% 压缩感知重构
y = Phi*X(:);
theta_est = zeros(2,1);
for ii = 1:2
a1 = exp(1j*pi*cosd(theta(ii))*(0:M-1)');
a2 = exp(1j*pi*sind(theta(ii))*(0:M-1)');
a = [a1; a2];
A = kron(eye(N), a);
alpha_est = l1eq_pd(y, A, [], Phi, 1e-5);
alpha_est = reshape(alpha_est, M, N);
[~, idx] = max(abs(alpha_est(:)));
[i_est, j_est] = ind2sub([M, N], idx);
theta_est(ii) = atan2d(pos(i_est,2), pos(i_est,1));
end
% 结果输出
fprintf('真实角度:[%f, %f]\n', theta(1), theta(2));
fprintf('估计角度:[%f, %f]\n', theta_est(1), theta_est(2));
```
其中,l1eq_pd是使用l1-magic工具箱中的函数实现的l1最小化求解器。
运行该代码可以得到真实DOA角度和压缩感知重构的DOA角度估计结果。