Controlled Tracking in Urban Terrain: Closing the Loop

TL;DR

This paper presents a closed-loop active sensing system for urban terrain that integrates detection, tracking, and adaptive waveform scheduling using multistatic radars, multiple motion models, and lookahead to improve target tracking accuracy.

Contribution

The paper introduces a novel closed-loop system combining multistatic radars, adaptive waveform scheduling, and multiple motion models for enhanced urban target tracking.

Findings

Effective in dense clutter and multipath environments

Improves tracking accuracy with adaptive waveform selection

Demonstrated via Monte Carlo simulations

Abstract

We investigate the challenging problem of integrating detection, signal processing, target tracking, and adaptive waveform scheduling with lookahead in urban terrain. We propose a closed-loop active sensing system to address this problem by exploiting three distinct levels of diversity: (1) spatial diversity through the use of coordinated multistatic radars; (2) waveform diversity by adaptively scheduling the transmitted waveform; and (3) motion model diversity by using a bank of parallel filters matched to different motion models. Specifically, at every radar scan, the waveform that yields the minimum trace of the one-step-ahead error covariance matrix is transmitted; the received signal goes through a matched-filter, and curve fitting is used to extract range and range-rate measurements that feed the LMIPDA-VSIMM algorithm for data association and filtering. Monte Carlo simulations demonstrate the effectiveness of the proposed system in an urban scenario contaminated by dense and uneven clutter, strong multipath, and limited line-of-sight.