Identification of acoustic MIMO systems: challenges and opportunities
Signal Processing
IEEE Transactions on Signal Processing
Blind separation of underwater acoustic signals
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
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This paper discusses a frequency domain method for blind identification of multiple-input multiple-output (MIMO) convolutive channels driven by white quasistationary sources. The sources can assume arbitrary probability distributions, and in some cases, they can even be all Gaussian distributed. We also show that under slightly more restrictive assumptions, the algorithm can be applied to the case when the sources are colored, nonstationary signals. We demonstrate that by using the second-order statistics of the channel outputs, under mild conditions on the nonstationarity of sources, and under the condition that channel is column-wise coprime, the impulse response of the MIMO channel can be identified up to an inherent scaling and permutation ambiguity. We prove that by using the new algorithm, under the stated assumptions, a uniform permutation across all frequency bins is guaranteed, and the inherent frequency-dependent scaling ambiguities can be resolved. Hence, no post processing is required, as is the case with previous frequency domain algorithms. We further present an efficient, two-step frequency domain algorithm for identifying the channel. Numerical simulations are presented to demonstrate the performance of the new algorithm.