Array Processing in Impulsive Noise: A Nonlinear Beamformer Based on the EM Algorithm

摘要

THe localization of multiple sourcesand the reception of the signals emitted by those sources is a central problem in sensor aray processing. Many approaches have been studies for this problem when the additive noise in the sensor array data is modeled with a Gaussian distribution, but these schemes typkally perform very poorly when the noise is non-Gaussian. A new algorithm is presented in this paper for array processing in non-Gaussian noise. The algorithm is based on modeling the noise with a Gaussian mixture distribution. The expectation-maximization algorithm is then used to derive an iterative processing structure that estimates the source locations, estimates the sourec waveforms, and adapts the processing to match the characteristics of the noise. The processing structure can be interpreted in terms of a "robust spatial power spectrum" and a "nonlinear beamformer" for the case of a single source. SImulation results for simgle and multiple-source scenarios indicate that the algorithm performs well in comparison with appropriate cramer-Rao bounds and other array processing methods.