Applications of cumulants to array processing part II: non-Gaussian noise suppression

The main motivation of using higher order statistics in signal processing applications has been their insensitivity to additive colored Gaussian noise. The main objection to those methods is their possible vulnerability to non-Gaussian noise. In this paper, we investigate the effects of non-Gaussian ambient noise on cumulant-based direction-finding systems using the interpretation for the information provided by cumulants for array processing applications described in the companion paper [4]. We first demonstrate the suppression of uncorrelated non-Gaussian noise that has spatially varying statistics. Then, we indicate methods to suppress spatially colored non-Gaussian noise using cumulants and an additional sensor whose measurement noise component is independent of the noise components of the original array measurements. We also indicate the noise suppression properties of the virtual-ESPRIT algorithm proposed in [4]. In addition, we propose a method that combines second- and fourth-order statistics together in order to suppress spatially colored non-Gaussian noise. Finally, we also illustrate how to suppress spatially colored non-Gaussian noise when the additional sensor measurement is not available. Simulations are presented to verify our results.