Approximate maximum-likelihood delay estimation via orthogonal wavelet transform

A novel approximate maximum likelihood algorithm is proposed for estimating the time difference of arrival between signals received at two spatially separated sensors. Prior to cross correlation, one of the channel outputs is optimally weighted at different frequency bands with the use of an orthogonal wavelet decomposition. It can be viewed as a time domain implementation of the generalized cross correlation method. However, it does not suffer from the performance degradation due to the errors inherent in spectral estimation obtained from finite length data and is computationally efficient. Simulation results show that the proposed method outperforms direct cross correlation particularly when the noise level is high