Locating RF emitters with large UAV teams
Paul Scerri, Robin Glinton, Sean Owens, Steven Okamoto, Katia P. Sycara · 2007
This chapter describes a principled, yet computationally efficient way for a team of UAVs with Received Signal Strength Indicator (RSSI) sensors to locate radio frequency emitting ground vehicles in a large environment. Such a capability has a range of both civilian and military applications. RSSI sensor readings are noisy and multiple emitters will cause ambiguous, overlapping signals to be received by the sensor. Generating a probability distribution over emitter locations requires integrating multiple signals from different UAVs into a Bayesian filter, hence requiring cooperation between the UAVs. To build a coherent distributed picture given communication limitations, the UAVs share only those sensor readings that induce the largest changes in their local filter. Each UAV translates its probability distribution into a map of information entropy and then plans a path that will maximize the reduction in entropy (or conversely provides the highest information gain.) Planned paths are shared with a subset of other UAVs to minimize overlapping search. Experiments in a medium fidelity simulation environment show the approach to be lightweight and effective. Live flight results with lightweight Class I UAVs validate our approach. 1