A new generalized quadratic correlation delay estimation algorithm based on PHAT-PR double weighting is proposed to address the problem of large delay estimation errors in existing delay estimation algorithms under low signal-to-noise ratio conditions. A new delay estimation algorithm is formed by first weighting the joint phase change (PHAT) algorithm based on the existing generalized quadratic correlation algorithm and second weighting the PR formed by combining PHAT and ROTH. In MATLAB, it was designed to simulate and compare it with traditional PHAT-GCC and PHAT weighting algorithm based on generalized quadratic correlation. The results showed that when the signal-to-noise ratio was greater than 0dB, the delay estimation errors of the three algorithms were not significantly different, and their performance was similar. After the signal-to-noise ratio was less than 0dB, the errors of PHAT-GCC and PHAT weighting algorithm based on generalized quadratic correlation increased rapidly, and their performance de