RIS-Aided Passive Detection for LSS Targets: A GNSS Multipath-Assisted Scheme

The complex topography of urban canyons with many reflectors and scatterers makes it challenging to detect low-altitude, smaller, and slow-speed targets. In this paper, we present a novel multipath-assisted passive detection scheme based on the global navigation satellite system signals in urban canyons. We first propose an information-level target detection scheme, where a binary hypothesis test is conducted according to variation in the received signal given the presence or absence of targets in the environment. To take usage of multipath components (MPCs) in the proposed scheme, we introduce virtual anchors to model reflected signals’ propagation paths. We also introduce the reconfigurable intelligent surface to artificially improve the reflective environment and enhance the quality of received MPCs. The detection performance indicators are analyzed theoretically. Simulation results show that the proposed schemes respectively reach 90% and 94% detection probability at a signal-to-noise ratio of 5 dB. The RIS-based method outperforms the multipath-assisted method when the RIS error is less than 0.41 m.

I. Introduction

Detection of low-altitude, smaller size, and slow-speed (LSS) targets represented by unmanned aerial vehicles gains increasing attention and interest in research. Abuses of drones such as smuggling, privacy violations, and espionage occur, and drone terrorist attacks and malicious flight disruptions have tremendous harm [1]. These inappropriate applications threaten public safety. Detection is the first step in dealing with LSS targets threats. Air target detection techniques can be broadly classified as either active or passive. Under active detection, a dedicated transmitter must control the transmitted signal, resulting in high costs and complex operations. Passive detection systems in which opportunity signals act as noncooperative illuminators involve low costs and energy consumption [2], making this approach more effective than active detection. The choice of the illuminator is fundamental to passive detection. Common opportunity signals that can be utilized as illuminators include digital video broadcasting (terrestrial) [3], Wi-Fi [4], long-term evolution [5], and the generation wireless systems [6]. These signals exhibit varying detection ranges and accuracy. Compared with the above illuminators, the global navigation satellite system (GNSS) can provide all-day global coverage due to its constellation design. This system is hence one of the most promising illuminators for passive detection. Using the GNSS as an illuminator offers advantages such as precise synchronizing performance, wideband with modernized signals, and a special microwave region (L-band) to reduce interference. The GNSS-based passive detection is recently employed in vessel target detection [7], [8], [9]. In [7], multiple GNSS satellites are used to detect and image a vessel target. Image processing is usually modeled as an optimization problem and solved using particle swarm optimization. The authors in [8] analyzed the possibility of identifying moving targets via a GNSS-based passive bistatic radar and verified the approach’s feasibility through experiments.