Micro-Doppler Based Mini-UAV Detection with Low-Cost Distributed Radar in Dense Urban Environment

Abstract

In recent years, the usages of consumer-grade mini-Unmanned Aerial Vehicles (mini-UAV, also called drones) are drastically increased. To detect and monitor the drone in a highly urbanised environment, a distributed radar system consisting of a group of low-cost small radar sensors is under study. In this paper, we present a micro-Doppler based automatic drone detection/classification system for the low-cost distributed radar sensors to effectively discriminate drones from other types of targets that are common in the urban area, such as vehicles, bicycles and walking persons. It consists of a two-step processing. The first step uses the complex cadence velocity diagram to extract the target micro-Doppler features and yields preliminary classification results. The second step jointly considers the current and previous N successive time segments to give the final determination. The two-step drone classification technique is implemented in our low-cost distributed radar demonstrator and tested in different locations of real environments. Promising drone classification results are demonstrated.