Optimal Formation of UAV Swarm for TDOA-Based Passive Target Tracking

An analytic solution to the optimal formation problem of an unmanned aerial vehicle (UAV) swarm is newly proposed for maximizing the perfomrance of passive target tracking. Most previous techniques could not handle this problem efficiently because they have had difficulties in defining the performance index of a nonlinear target tracking filter in closed form. To overcome this limitation, the passive target tracking problem is investigated within the framework of the linear non-conservative robust Kalman filter (NCRKF) theory. Accommodating the merit of the suggested linear target tracking filter structure, its performance measure can be analytically expressed in terms of the UAV formation as well as the sensor accuracy. Therefore, it is easy to determine the optimal UAV formation by maximizing the target tracking performance in the worst case. In addition, our approach is very practical because it considers the estimation error characteristics of the actual passive target tracking filter and the communication range among UAVs in determining the optimal UAV formation. Through the simulations, the effectiveness of the proposed scheme is validated.