Closed-form direction finding and polarization estimation with arbitrarily spaced electromagnetic vector-sensors at unknown locations

TLDR

The commercially available vector‑sensor measures all six electromagnetic‑field components with six colocated but diversely polarized antennas, and this method refines earlier work by Li (1993). This paper introduces a new closed‑form ESPRIT‑based algorithm for multisource direction finding and polarization estimation with arbitrarily spaced electromagnetic vector‑sensors whose 3‑D locations need not be known. ESPRIT exploits nonspatial interrelations among the six unknown field components to produce eigenvalues from which the source’s electromagnetic‑field vector is estimated up to a complex scalar, and a vector cross‑product then yields an unambiguous estimate of the source’s normalized Poynting vector and its Cartesian direction cosines. Monte‑Carlo simulations verify the efficacy and versatility of this innovative scheme.

Abstract

This paper introduces a new closed-form ESPRIT-based algorithm for multisource direction finding and polarization estimation with arbitrarily spaced electromagnetic vector-sensors whose three-dimensional (3-D) locations need not be known. The vector-sensor, already commercially available, consists of six colocated but diversely polarized antennas separately measuring all six electromagnetic-field components of an incident wavefield. ESPRIT exploits the nonspatial interrelations among the six unknown electromagnetic-field components of each source and produces from the measured data a set of eigenvalues, from which the source's electromagnetic-field vector may be estimated to within a complex scalar. Application of a vector cross-product operation to this ambiguous electromagnetic-field vector estimate produces an unambiguous estimate of that source's normalized Poynting vector, which contains as its components the source's Cartesian direction cosines. Monte Carlo simulation results verify the efficacy and versatility of this innovative scheme. This novel method maybe considered as a simplification and a refinement over Li's (1993) work.