Rényi Entropy-Based Adaptive Integration Method for 5G-Based Passive Radar Drone Detection

Abstract

This paper presents the first successful drone detection results using a 5G network as a source of illumination in a passive radar system. Furthermore, a novel adaptive strategy for signal integration is shown. The proposed approach is based on the Rényi entropy. It allows one to select time frames with a densely allocated downlink channel both in the time and frequency domains. The resource allocation is strongly related to a network load and has a crucial influence on 5G-based passive radar range resolution and detection capabilities. The proposed technique was validated using simulated and real-life signals, confirming the possibility of detecting unmanned aerial vehicles (UAVs) in 5G-network-based passive radars. Moreover, the proposed methodology can be directly used in passive radar systems where the illuminating signal duration and bandwidth are content-dependent, and the radar resolution may vary significantly.

Keywords

• passive bistatic radar (PBR)
• 5G
• passive coherent location (PCL)
• entropy
• UAV