Passive acoustic localization using blind Gauss Markov estimate for the time delay vector

This is the authors' abstract. We don't add key points for this paper.

Time delay estimation has important applications in the fields of radar, sonar, seismology, multimedia communication etc. For a distant, stationary radiating source, the optimum time delay vector estimation at a receiving sensor array is realized using Generalized Cross Correlation (GCC) function and its error matrix, expressed in terms of apriori known source signal and sensor background noise spectra. This gives a linear minimum variance unbiased estimate known as the Gauss Markov Estimate. This paper examines the use of Power Spectral Density (PSD) estimation based Gauss Markov Estimate for cases of unknown source spectra and gives a two step time delay estimation algorithm for close range sources. The technique has been analyzed for a three element linear array with wideband source and shows improvement in terms of mean square error (MSE) for inter-sensor time delays, source range and bearing. The corresponding PSD estimation error has been expressed in terms of the spectral distortion measure.