Passive Localization Based on Spectral Estimation Methods Using Sources of Opportunity

Passive localization methods based on Double-Correlation Function (DCF) can localize an unknown source by matching the signal-correlated structures extracted from correlation function of source signal received at two sensors, as the structures are dependent on the position of the source and the waveguide. It is similar to classical matched field processing, but differs in that data-based measured replicas are used instead of modeled replicas, and the signal-correlated structures are matched rather than acoustic field. This paper presents an extension of this method from time domain to frequency domain, by utilizing generalized cross-correlation spectral estimation methods to normalize the cross-correlation function. The analysis based on air experiment shows that the proposed algorithm has significant improvements against interference and on the estimation accuracy.