Passive Polarimetric Multistatic Radar Detection of Moving Targets

TL;DR

This paper investigates how polarimetric diversity can enhance passive multistatic radar detection of moving targets by modeling targets as collections of dipoles and developing detection and estimation methods.

Contribution

It introduces a novel data model incorporating polarization and anisotropy, and develops detection and dipole estimation techniques for passive multistatic radar.

Findings

Polarimetric diversity improves detection performance.

The proposed methods effectively estimate target dipole moments.

Numerical simulations validate the approach's effectiveness.

Abstract

We study the exploitation of polarimetric diversity in passive multistatic radar for detecting moving targets. We first derive a data model that takes into account polarization and anisotropy of targets inherent in multistatic configurations. Unlike conventional isotropic models in which targets are modeled as a collection of uniform spheres, we model targets as a collection of dipole antennas with unknown directions. We consider a multistatic configuration in which each receiver is equipped with a pair of orthogonally polarized antennas, one directed to a scene of interest collecting target-path signal and another one having a direct line-of-sight to a transmitter-of-opportunity collecting direct-path signal. We formulate the detection of moving target problem in a generalized likelihood ratio test framework under the assumption that direct-path signal is available. We show that the result can be reduced to the case in which the direct-path signal is absent. We present a method for estimating the dipole moments of targets. Extensive numerical simulations show the performance of both the detection and the dipole estimation tasks with and without polarimetric diversity.