A Joint Spatial-Polarization Normalized LMS Based on Circular Array

Abstract

In order to solve the problem that the spatial filtering fails when the Direction of Arrival (DOA) of the desired signal and the interference signal are same or similar, first, the polarization array vector is introduced into the spatial filtering algorithm-Least Mean Square (LMS) to form the Spatial-Polarization Least Mean Square (SPLMS); then in order to overcome the contradiction between the convergence speed and steady-state error of the SPLMS, Spatial-Polarization Normalized Least Mean Square (SPLMS) is useed to improve this problem. Finally, a simulation analysis of the error curve of the SPLMS and the SPNLMS is carried out, and it is found that when the DOA of both signals are same or similar, the SPLMS can achieve a good beamforming effect. The steady-state error accuracy is obviously improved. The convergence speed is faster, stronger, and it is more superior than the SPLMS.