matlab_基于自相关算法的通信系统中微弱信号检测程序

% Autocorrelation function detection clear all close all fs=10000; N=1000; x=0:1/fs:(fs-1)/fs; y0=sin(2*pi*1000*x); n=fs; x1=normrnd(0,1,1,n); %散粒噪声 lamdac=2;Tmaxc=1000; ic=1;Tc(1)=random('exponential',lamdac); while(Tc(ic)<Tmaxc) Tc(ic+1)=Tc(ic)+random('exponential',lamdac); ic=ic+1; end Tc(ic)=Tmaxc;xc=0:1:ic;wc(1)=0; for pc=1:ic wc(pc+1)=Tc(pc); end tc=(1/fs:1/fs:1)*Tmaxc; ac=0.1; Wc=fs/Tmaxc*wc; Wc=floor(Wc); yc=zeros(length(Wc)-1,fs); for k1c=2:1:length(Wc); kc=Wc(k1c); t1c=1:1:fs; ypc=exp(-(t1c-kc)*ac); for kpc=1:1:kc-1 ypc(kpc)=0; end yc(k1c-1,:)=ypc; end x2=zeros(1,fs); for k2c=1:1:fs x2(1,k2c)=sum(yc(:,k2c)); end % 高斯色噪声 p=0.5; f0=0.05; a1=-2*p*cos(2*pi*f0); a2=p^2; x3=zeros(1,n); for i=3:1:n; x3(i)=a1*x3(i-1)-a2*x3(i-2)+x1(i); end % 混合噪声形成 y=y0+x1; yfft=abs(fftshift(fft(y))); f=(-length(yfft)/2:(length(yfft)/2-1))*fs/length(yfft); figure(1) plot(x,y) ylabel('幅值'); xlabel('时间'); title('混合信号时域波形'); figure(2) plot(f,yfft) ylabel('yfft'); xlabel('f'); title('混合信号频谱'); % 计算输入信噪比 snr1=0; ps1=sum(sum((y0-mean(mean(y0))).^2)); pn1=sum(sum((y-y0).^2)); snr1=abs(10*log10(ps1/pn1)); ys=y; % 一重自相关 [y1,lags]=xcorr(ys,'unbiased'); t=((-length(lags))/2/length(lags):1/length(lags):(length(lags)/2-1)/length(lags))*2; ys1=2*y1; figure(6) plot(t,ys1) ylabel('幅值'); xlabel('时间'); title('自相关输出'); % 计算自相关输出信噪比 fs1=2*fs; ts1=0:1/fs1:(fs1-2)/fs1; yr1=sin(2*pi*2*1000*ts1); snr2=0; ps2=sum(sum((yr1(5000:15000)-mean(mean(yr1(5000:15000)))).^2)); pn2=sum(sum((ys1(5000:15000)-yr1(5000:15000).^2))); snr2=abs(10*log10(ps2/pn2)); % 二重自相关 [y2,lags]=xcorr(ys1,'unbiased'); t1=((-length(lags))/2/length(lags):1/length(lags):(length(lags)/2-1)/length(lags))*4; ys2=2.2*y2; figure(7) plot(t1,ys2) ylabel('幅值'); xlabel('时间'); title('二重自相关输出'); % 计算二重相关输出信噪比 fs2=4*fs; ts2=0:1/fs2:(fs2-4)/fs2; yr2=sin(2*pi*1000*ts2); snr3=0; ps3=sum(sum((yr2(10000:20000)-mean(mean(yr2(10000:20000)))).^2)); pn3=sum(sum((ys2(10000:20000)-yr2(10000:20000))).^2); snr3=abs(10*log10(ps3/pn3));