MAXIMUM LIKELIHOOD DOA ESTIMATOR BASED ON PARTICLE FILTERING

摘要

Maximum Likelihood Estimator (MLE) has been shown to be the best performance in Direction-Of-Arrival (DOA) estimation.However, the computational burden of a multidimensional grid search for MLE is very large.In order to resolve the question of computation burden, particle filtering methods are combined with maximum likelihood DOA estimator.A novel Maximum Likelihood DOA Estimator based on Particle Filtering (MLE-PF) is proposed.Numerical simulations illustrate the fact that MLE-PF keeps the perfect performance of MLE and reduces the computational complexity of MLE from O(Lk) to O(K×Ns).Also MLE-PF performs better than MUSIC and MiniNorm, especially in low SNRs.