Towards ISAC RIS-Enabled Passive Radar Target Localization

TL;DR

This paper proposes a novel passive radar localization method using RIS-enabled ISAC in 6G networks, demonstrating improved target detection and a significant dynamic range reduction through an iterative AoA estimation algorithm.

Contribution

It introduces a normalized least mean squares algorithm for joint target detection and AoA estimation in RIS-assisted passive radar systems, enhancing localization accuracy.

Findings

Achieved a 14 dB dynamic range reduction at the passive radar.

Demonstrated effective joint detection and AoA estimation through simulations.

Validated the proposed method's capability in weak signal scenarios.

Abstract

Incorporating integrated sensing and communication capabilities into forthcoming 6G wireless networks is crucial for achieving seamless synchronization between the digital and physical worlds. The following paper focuses on a scenario where a passive radar (PR) is subject to weak line-of-sight signals of opportunity, emanating from an access point and subsequently reflecting off targets, ultimately reaching the PR. Furthermore, a normalized least mean squares method is presented for jointly detecting the number of targets and estimating target angles of arrival (AoAs). The algorithm iteratively adjusts the steering vector estimates to minimize a suitable error cost function, while the target AoAs are identified via a peak-finding search conducted on the resulted power spectrum. Simulation results show the capabilities of the proposed localization method, as well as a 14 dB dynamic range reduction that can be achieved at the PR.