Autonomous UAV Search for an RF Source in Urban Environments

This paper presents a cognitive search strategy that enables new possibilities to study autonomous search for an emitting source in an urban environment through the efficient gathering of location information at temporal and spatial granularities not possible with classical search methods. In this study, we develop an online unmanned aerial vehicle (UAV) path-planning strategy for autonomous search and localisation of emitting source. The UAV is equipped with Receiver Signal Strength (RSS) sensors to localise stationary radio frequency (RF) emitter. A high fidelity non-linear measurement model of RF propagation in urban environment is adopted for this purpose. Source localisation is carried out using a particle filtering method, while a partially observable Markov decision process is applied for dynamic path planning. This approach allows autonomous navigation of a UAV in a direction of maximum information gain to locate the emitter and reduce exploration time. We also employ the concept of search termination criteria to maximise the accuracy of the source localisation and validate the effectiveness of the proposed online approach through extensive simulations. The numerical results show the feasibility of the proposed approach.