Direction finding in non-Gaussian impulsive noise environments
Digital Signal Processing
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The importance of extending the statistical array signal processing methodology to what we call the alpha-stable framework is apparent. First, scientists and engineers have started to appreciate infinite moments and the elegant scaling and self-similarity properties of stable distributions. Additionally, real life applications exist in which impulsive channels tend to produce large-amplitude, short-duration interferences more frequently than Gaussian channels do. The stable law has been shown to successfully model noise over certain impulsive channels. In this paper, we study the problem of localizing wide-band sources in the presence of noise modeled as a complex isotropic stable process. We consider the frequency-domain representation of the sensor outputs and show that the spectral density of complex stable processes plays a role, in array processing problems, analogous to that played by the power spectral density of second-order processes.