On pre-filtering strategies for the GCC-PHAT algorithm
Hong-Goo Kang, Michael Graczyk, Jan Skoglund · 2016
In this paper, we investigate the impact of the pre-filtering method to generalized cross-correlation (GCC) based direction of arrival (DOA) estimation. The role of pre-filtering is either to emphasize or deemphasize certain frequency components before computing cross power spectrum. However, its impact or relation to environmental variation, e.g., in noisy environments, has not been clearly studied yet. An efficient pre-filter should consider the relative importance of individual frequency components and adaptively change its related parameters based on environmental variations. We first investigate the relationship between conventional pre-filtering functions and power normalization factors and its dependency on signal-to-noise-ratio (SNR) in various noisy environments. Then, we experimentally show that it is helpful to introduce a Wiener-like gain function into the pre-filtering process to efficiently design a generalized rule to determine control parameters. By analyzing the importance of parameter estimation errors in the estimation of Wiener filter parameters, e.g. noise power spectral density (PSD) and the a priori SNR, this paper proposes an efficient estimation strategy to design a pre-filter for robust GCC based DOA estimation.