Localization of Multiple Targets with Identical Radar Signatures in Multipath Environments with Correlated Blocking

TL;DR

This paper develops a Bayesian framework and a polynomial-time algorithm for localizing multiple targets with identical radar signatures in complex multipath environments with correlated blocking, highlighting the importance of modeling environmental correlations.

Contribution

It introduces a tractable approximation for multi-target localization considering correlated blocking and proposes a sub-optimal algorithm evaluated through simulations.

Findings

Correlated blocking significantly impacts detection performance.

Assuming independent blocking leads to higher false alarms.

The proposed method improves localization accuracy in challenging environments.

Abstract

This paper addresses the problem of localizing an unknown number of targets, all having the same radar signature, by a distributed MIMO radar consisting of single antenna transmitters and receivers that cannot determine directions of departure and arrival. Furthermore, we consider the presence of multipath propagation, and the possible (correlated) blocking of the direct paths (going from the transmitter and reflecting off a target to the receiver). In its most general form, this problem can be cast as a Bayesian estimation problem where every multipath component is accounted for. However, when the environment map is unknown, this problem is ill-posed and hence, a tractable approximation is derived where only direct paths are accounted for. In particular, we take into account the correlated blocking by scatterers in the environment which appears as a prior term in the Bayesian estimation framework. A sub-optimal polynomial-time algorithm to solve the Bayesian multi-target localization problem with correlated blocking is proposed and its performance is evaluated using simulations. We found that when correlated blocking is severe, assuming the blocking events to be independent and having constant probability (as was done in previous papers) resulted in poor detection performance, with false alarms more likely to occur than detections.