Finding optimal trajectory points for TDOA/FDOA geo-location sensors

In emitter geo-location estimation systems, it is well known that the geometry between sensors and the emitter can seriously impact the accuracy of the location estimate. Here we consider a case where a set of sensors is tasked to perform a sequence of location estimates on an emitter as the sensors progress throughout their trajectories. The goal is to select the trajectories so as to optimally improve the location estimate at each step in the sequence. To build the optimal trajectories, the aircraft, at their current locations, need to know their optimal next states at the time of next estimation, under the constraint of a reachable set due to limited reachable velocity or thrust. In this paper, we propose a one-step method to tackle the optimal next state (ONS) problem using the particle swarm optimization (PSO) by solving the optimal amount of applied thrust along the flying trajectories. Simulation results show that the proposed method dramatically improves the estimation accuracy along the flying trajectories, compared to the random walk and constant velocity scheme. We also show that the estimation accuracy performance is also insensitive to the problem dimensionality.