Robust 3-D AOA Localization Based on Maximum Correntropy Criterion With Variable Center

Keyuan Hu, Wenxin Xiong, Zhi-Yong Wang, Hing Cheung So, Chi-Sing Leung

Abstract: This contribution investigates the problem of three-dimensional (3-D) angle-of-arrival (AOA) source localization (SL) in the presence of symmetric $\alpha$-stable ($\mathcal{S\alpha S}$) impulsive noise for $\alpha\in(0,2]$. The azimuth and elevation angle measurements are initially rewritten into a pseudolinear form using spherical coordinate conversion, thereby making them more manageable. Subsequently, we adopt the maximum correntropy criterion with variable center (MCC-VC) to devise a robust 3-D AOA location estimator that functions effectively without the prior knowledge of parameters governing the impulsiveness and dispersion of $\mathcal{S\alpha S}$ noise distributions. While it gives rise to a straightforward alternating minimization algorithmic framework, our analysis reveals that solely embracing MCC-VC leads to bias issues stemming from the correlation between the measurement matrix and noise. Aiming at addressing such a challenge, we introduce instrumental variables (IVs) to develop a bias-reduced maximum correntropy criterion (MCC) estimator, termed MCC with IV (MCC-IV). Simulation results illustrate a considerable performance enhancement of MCC-IV compared to existing schemes for 3-D AOA SL, particularly in achieving mean square error much closer to the Cramér–Rao lower bound and mitigating bias substantially.