Hyperbolic Function Based DOA Estimator in the Presence of Impulsive Noise

In this paper, a novel method is proposed for direction of arrival (DOA) estimation in the presence of impulsive noise. By introducing the hyperbolic secant function into the framework, a novel DOA estimator is designed. Based on the proposed estimator and low-rank decomposition, a robust subspace is obtained through alternative optimization. DOA estimation is achieved by applying the multiple signal classification (MUSIC) algorithm to the derived subspace. A detailed optimization procedure is outlined, and the convergence of the proposed estimator is proven. Comprehensive simulation results demonstrate that the proposed method could achieve superior performance in impulsive noise environments, especially under strongly impulsive conditions.