The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-249

“Applications of Cumulants to Array Processing Part II: Non-Gaussian Noise Suppression”

by Mithat C. Dogan and Jerry M. Mendel

February 1994

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 report (SIPI Report No. 247). 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. In addition, we propose a method that combines second-and fourth-order statistics together in order to suppress spatially-colored non-Gaussian noise. We also illustrate how to suppress spatially colored non-Gaussian noise when the additional sensor measurement is not available. We finally indicate the noise suppression properties of the virtual-ESPRIT algorithm proposed in (SIPI Report No. 247). Simulations are presented to verify our results.

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