Abstract

We present a novel direction finding algorithm based on least squares error in the presence of heavy-tailed noise. We develop the weighted least squares error using array data only, which we call auto-weighted least squares. We propose a unity snapshot infinite norm weighted scheme. The auto-weighted least squares is itself standard least squares. In simulations, we model the noise as an /spl alpha/-stable distribution, and the performance of the proposed algorithm is superior to related algorithms.

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