Taming and Leveraging Interference in Mobile Radar Networks

TL;DR

This paper addresses interference challenges in mobile radar networks, proposing methods for detection, mitigation, and leveraging interference to improve radar performance in dense environments.

Contribution

It introduces novel interference management techniques and explores how interference can be used to infer additional information in vehicular radar networks.

Findings

Proposed algorithms effectively detect and mitigate interference.

Simulations show improved radar performance in dense networks.

Interference can be leveraged to extract useful information.

Abstract

Mobile radar networks, such as autonomous driving systems, are subject to the severe challenge of mutual interference. Despite the inborn interference-proof capability in frequency modulation continuous waveform (FMCW) radar, interference management is necessary for dense radar networks. The approaches combatting the radar interference include the timing diversity of waveform parameters, data-driven detection interference, and signal processing based decoupling of interference. Moreover, the leverage of radar interference for inferring the information of interfere is studied. Simulations are carried out in the scenario of radar interferences in vehicular networks, which demonstrates the performance of the proposed algorithms.