Differentiation and Localization of Ground RF Transmitters Through RSSI Measures From a UAV

Abstract

Low-altitude Unmanned Aerial Vehicles (UAVs) are a valuable solution for data gathering, surveillance, warfare, and mapping. In these applications, differentiating and estimating the position of ground Radio Frequency (RF) emitters is pivotal. In order to achieve this, we define an experimental setup based on Received Signal Strength Indicator (RSSI) collected by a single UAV at different points of a predefined trajectory. The experimental setup is evaluated for the two unlicensed frequency bands of $\mathbf {2.4}\,$GHz and $\mathbf {865}\,$MHz with and without interference, respectively. We show that the application of the maximum likelihood algorithm to the RSSI measures collected in experiments conducted in rural areas gives a mean absolute localization error of about $5\,$m and $4\,$ m for a single transmitter with and without interference, respectively. A threshold-based technique is proposed to improve the accuracy in the presence of interference. For multiple transmitters, the RSSI data are divided into clusters and fed into a localization algorithm. A k-means clustering algorithm eliminates user intervention and identifies the number of RF emitters in the area. As a further contribution of the paper, we performed a validation phase where the UAV flight path and data collection are simulated using the QuaDRiGa realistic radio impulse channel model.