Real-Time Optimized Trajectories for 2D Emitter Localization using a UAVs team

.The benefits of using multiple unmanned aerial vehicles (UAV) platform to perform certain tasks include increased robustness in the system, greater flexibility, reduced cost, as well as an increase in the speed of task completion. By acting collectively, a team of UAVs can quickly determine the approximate location of intermittently broadcasting RF emitters with simple passive angle-of-arrival sensors. Passive ground emitter location techniques are vital to electronic warfare system (EWS) providing threat warnings in hostile environments. The paper focuses on proposing and evaluating solutions for optimizing the UAV trajectories for localization of a RF emitter using Line of Bearing (LOB) measurements. The optimization approach aims to minimize the size of the target position error ellipse. A framework using only the geometry of the problem is explored to minimize the maximal bounds of the emitters’ locations without using a belief or probability distribution needed for iterative approaches, which requires a good initial guess to ensure convergence on the true position. The effectiveness of the geometric approach is shown by designing and evaluating a global decision-making strategy based on Learning Real-Time A* (LRTA*) algorithm. Through simulations, the search solution is compared to a conventional optimal control solution approach for a two dimensional space case. The LRTA* solution achieves acceptable accuracy with sufficient observation points and it is suitable for real-time purposes. The solution is also attractive for its capability to initialize iterative algorithms if needed.