AR models for wideband source location

Abstract

Wideband source location in array signal processing has received much attention in the literature lately. Methods such as the Coherent Signal Subspace (CSS) method proposed by Wang and Kaveh [12], and the signal subspace method used by Cadzow [3], are typical of the approaches used to tackle the multiple wideband source location problem. Most of these methods are variations of the narrowband high-resolution methods. Grenier [5], on the other hand, has applied the idea of time-dependent Auto-Regressive (AR) modeling [7] for a nonstationary process to the frequency domain AR modeling of the sensor outputs in a linear array and has been able to produce good results for a wideband signal. The AR coefficients in the model are expanded in a set of frequency-dependent basis functions. The choice of the basis functions was deemed immaterial and the method works even when only one snapshot of the array output is available. In this paper, we re-examine this method and present an extension of the frequency-dependent AR modeling approach to a planar array. It is shown that the use of a set of sinc functions for representing the frequency-dependent AR coefficients accurately tracks their evolution in the frequency domain, and gives superior performance compared to that when power or Legendre functions are used. We also propose two methods for smoothing the spatial spectra, from which the source locations are determined. Comparison with the CSS method are also presented.