Design and performance evaluation of a localization system to locate unwanted drones by using wireless signals

The use of consumer drones has increased greatly in the last few years. It is important in many situations to be able to determine the location of unwanted drones for the sake of privacy, security, and safety. In this paper, a localization system is designed to determine the location of an unwanted drone in an outdoor line of sight (LOS) situation by using its wireless signal transmitted for communication with the controller. Two algorithms using the received signal strength (RSS) of the unwanted drone, the recursive least squares (RLS) algorithm and an improved maximum likelihood estimation (MLE), are implemented. Experiments are conducted in the open areas of the university campus to obtain a 3D RF empirical propagation model and this channel model is used in the algorithms. The performance of the two algorithms are compared with each other and with the Cramer-Rao Lower Bound (CRLB). By analyzing the results, we conclude that the improved MLE algorithm performs better than the RLS in our localization system. We also discuss the challenges that we will face in the future to improve our system.