Polarization-beamspace self-initiating MUSIC for azimuth/elevation angle estimation

A novel MUSIC-based (multiple signal classification) direction finding algorithm applicable to arbitrary three-dimensional arrays of electromagnetic vector-sensors is herein proposed. This innovative algorithm: (1) self-generates coarse estimates of the arrival angles to start off its MUSIC-based iterative search without any a priori information on the sources´ parameters, (2) exploits the sources´ polarization diversity, (3) decouples the estimation of the sources´ arrival angles from the estimation of the sources´ polarization parameters, and (4) automatically pairs the x-axis direction-cosine estimates with the y-axis direction-cosine estimates and with the polarization estimates. An electromagnetic vector-sensor is composed of six co-located diversely polarized antennas distinctly measuring all six electromagnetic-field components of a multi-source incident wave-field and is commercially available. This proposed algorithm forms polarized beams at each vector-sensor, based on coarse estimates of each source´s respective electromagnetic-field components obtained by decoupling the signal-subspace eigenvectors. Simulation results verify this innovative scheme´s capability to self-generate initial estimates for its MUSIC-based iterative search and demonstrate the proposed algorithm´s superior performance relative to a similarly spaced array of unpolarized scalar sensors. Under one scenario, the proposed method lowers the estimation bias by 98% and the estimation standard deviation by 40%