data_omp.rar_作弊信号 matlab_信号检测

clear all; clc; load('1-1. SAVED-2013.09.06_(426,434MHz,500ms, 430MHz-1s5s ).mat'); Y = Y1; BW = 20e6; fs = 25e6; M = 300; sparsity = 10; N = 1024*4; delta_t = N/fs; delta_f = BW/N; % N=8192; % delta_t=317.68*10^(-6); % delta_f=3.0518e3; % N=2048; % delta_f=6.1e3; % delta_t=163.84*10^(-6); % NumofSamples=N/64; loop=floor(length(Y)/N); result=zeros(sparsity,loop); for i=1:2000 X_data=zeros(N,1); Y_data_temp=Y(N*(i-1)+1:N*i); [val1,pos1]=sort(rand(N,1)); index_samples=sort(pos1(1:M)); IDFT_Matrix=ifft(eye(N,N)); CS_Matrix=IDFT_Matrix(index_samples,:); Y_data=Y_data_temp(index_samples,:); X_index=zeros(1,sparsity); Y_data_residual=Y_data; CS_Matrix_col=[]; %%由CS_Matrix的列所构成的矩阵 初始化为空矩阵 product=zeros(1,N); for loop_col=1:N product(loop_col)=abs(dot(Y_data_residual,CS_Matrix(:,loop_col))); end [val product_temp] = sort(product,'descend'); pos=product_temp(1:sparsity); CS_Matrix_col=[CS_Matrix_col CS_Matrix(:,pos)];%%记录相关性最大的列 X_data_nonzero=((CS_Matrix_col'*CS_Matrix_col)^(-1))*(CS_Matrix_col')*Y_data; %%最小二乘 Y_data_residual=Y_data-CS_Matrix_col*X_data_nonzero; X_index=pos;%%记录X_data中非零元素的位置 X_data(X_index,1)=X_data_nonzero; for ii=1:sparsity if abs(X_data(X_index(ii),1))^2/N<0.1 X_index(ii)=0; end end fre_eve=X_index(X_index~=0); result([1:length(fre_eve)],i)=sort(fre_eve'); end for loop1=1:loop for loop2=1:10 if result(loop2,loop1)~=0 result(loop2,loop1)=(result(loop2,loop1)-0.5)*delta_f*10^(-6)+420; end end end plot([1:loop]*delta_t,result,'b.'); axis([0 5 420 440]);