Complex Total Maximum Versoria Criterion Algorithm for DOA Estimation
Haiquan Zhao, Yi Peng, Wenjing Xu
Abstract
In bias-compensated models that include input noise, existing adaptive algorithms exhibit severe performance degradation in direction-of-arrival (DOA) estimation when the signal is disturbed by impulsive noise. But at this situation, the Versoria term in the MVC function is approximated to be zero, which can eliminate the likelihood of updating the weight vector based on wrong information. Therefore, in this brief, by searching for the peaks of the spatial spectrum to update the weights, and estimate the direction of the angle of arrival, complex total maximum Versoria criterion algorithm (CTMVC) is proposed. Furthermore, the local stability of the algorithm in the complex domain is analyzed and the convergence range of the step size is derived. Simulation results show that the algorithm is robust to impulsive noise and outperforms other adaptive algorithms.