A novel correntropy based DOA estimation algorithm in impulsive noise environments

• We model the impulsive noises in array signal processing as complex SαSSαS processes.
• We examine the inherent robustness to outliers of correntropy.
• We propose the statistics CRCO (correntropy based correlation) for SαSSαS random variables.
• We define the CRCO based matrix for the array sensor outputs.
• We apply the CRCO based matrix with MUSIC to obtain DOA estimates.

The Direction of Arrival (DOA) estimation under impulsive noise environments remains open in the field of array signal processing. Inspired by the advantage of correntropy which exhibits a ‘robust statistics’ property, this paper proposes a new operator, namely, the correntropy based correlation (CRCO), for independent and identically distributed (i.i.d) symmetric alpha-stable (SαS)(SαS) random variables. We define the CRCO based matrix for the array sensor outputs and show that it can be applied with MUSIC to estimating DOAs in the presence of complex symmetric alpha-stable noise. The comprehensive Monte-Carlo simulation results demonstrate that CRCO–MUSIC outperforms the existing fractional lower order statistics (FLOS) based MUSIC algorithms especially in highly impulsive noise environments.