Optimal cooperative placement of GMTI UAVs for ground target tracking

TLDR: In this article, the Fisher information, obtained from the information form of Riccati equation, is used in the objective function, and the optimal sensor placement problem is solved by a combination of deterministic as well as randomized optimization.

Abstract: With the recent advent of moderate-cost unmanned (or uninhabited) aerial vehicles (UAV) and their success in surveillance, it is natural to consider the cooperative management of groups of UAVs. The problem considered in this paper is the optimization of the information obtained by a group of UAVs carrying out surveillance of several ground targets distributed over a large area. The UAVs are assumed to be equipped with ground moving target indicator (GMTI) radars, which measure the locations of moving ground targets as well as their radial velocities. In this research, the Fisher information, obtained from the information form of Riccati equation, is used in the objective function. Sensor survival probability and target detection probability for each target-sensor pair are also included in the objective function. The optimal sensor placement problem is solved by a combination of deterministic as well as randomized optimization. Simulation results on two different scenarios are presented for four different types of prior information.