Optimum cooperative UAV sensing based on Cramer-Rao bound

We investigate optimal estimation for both the position and the velocity of the ground moving target (GMT) by employing sensors composed of unmanned aerial vehicles (UAVs). The problem is the cooperative sensing by the UAVs, in terms of their location geometries to achieve optimal estimation of the GMT. Based on the Cramer-Rao bound, we are able to derive the minimum achievable error variance in estimation of the position and the velocity of the GMT, and obtain the optimal geometries of the UAV sensors via minimization of the minimum achievable error variance for unbiased estimation commanded by the Cramer-Rao bound. Our solution is complete that encompasses various situations for the GMT, and the number of UAV sensors.