就像您说的那样，取fft并逐点乘以其复共轭，然后使用反fft(或者在两个信号互相关的情况下) :Corr(x,y) <=> FFT(x)FFT(y)*)

Just like you stated, take the fft and multiply pointwise by its complex conjugate, then use the inverse fft (or in the case of cross-correlation of two signals: Corr(x,y) <=> FFT(x)FFT(y)*)

x = rand(100,1);
len = length(x);

%# autocorrelation
nfft = 2^nextpow2(2*len-1);
r = ifft( fft(x,nfft) .* conj(fft(x,nfft)) );

%# rearrange and keep values corresponding to lags: -(len-1):+(len-1)
r = [r(end-len+2:end) ; r(1:len)];

%# compare with MATLAB's XCORR output
all( (xcorr(x)-r) < 1e-10 )

实际上，如果您看一下xcorr.m的代码，这就是它的作用(只是它必须处理填充，规范化，向量/矩阵输入等的所有情况)

In fact, if you look at the code of xcorr.m, that's exactly what it's doing (only it has to deal with all the cases of padding, normalizing, vector/matrix input, etc...)