A novel cauchy score function based DOA estimation method under alpha-stable noise environments

Based on the study of alpha-stable distribution and its score function, by combining M-estimation theory and maximum likelihood estimation theory, this paper proposes a novel Cauchy score function based cost function of the residual fitting error matrix. And then, this cost function is employed as a substitute for the l(p)-norm based cost function of the residual fitting error matrix which is utilized in the l(p)-MUSIC algorithm. To solve the cost function, alternating convex optimization is applied. And the complex-valued Newton's method with optimal step size is developed to solve the resulting convex problem. With the obtained signal subspace, the direction of arrival (DOA) estimates are retrieved by the MUSIC technique. Comprehensive simulation results demonstrate that, the proposed algorithm can achieve more robust performance than its counterpart both in terms of resolution probability and root mean square error (RMSE), especially when the generalized signal to noise ratio (GSNR) is fairly low, or the underlying noise is extremely impulsive. (C) 2017 Elsevier B.V. All rights reserved.