Self-Initiating MUSIC-Based Direction Finding and Polarization Estimation in Spatio-Polarizational Beamspace

A novel self-initiating multiple signal classification (MUSIC)-based direction-finding (DF) and polarization-estimation algorithm in spatio-polarizational beamspace is herein presented for an arbitrarily spaced array of identically oriented electromagnetic vector sensors. An electromagnetic vector sensor, already commercially available, is composed of six colocated, but diversely polarized, antennas distinctly measuring all six electromagnetic-field components of a multisource incident wave field. This proposed algorithm: 1) exploits the incident sources’ polarization diversity; 2) decouples the estimation of the sources’ arrival angles from the estimation of the sources’ polarization parameters; 3) uses ESPRIT on pairs of vector sensors to self-generate coarse estimates of the arrival angles to start off its MUSIC-based iterative search without any a priori information on the incident sources’ parameters; 4) estimate the sources’ polarization states; and 5) automatically pairs the -axis direction-cosine estimates with the -axis direction-cosine estimates and with the polarization estimates. Monte Carlo simulation results verify the efficacy of the proposed method.