A Ground Target Tracking Approach for UAVs with Intermittent Measurements

A tracking algorithm using Bayesian filter and hospitability map (BF-HMap) is proposed to deal with the ground target tracking problem for unmanned aerial vehicles (UAVs) with intermittent measurements. The hospitability map, which describes the terrain-dependent motion capability of ground targets, is built through a centerline-and-gradient-based road detection method. The posterior probability density function (PDF) of the target state is maintained on-line through a Bayesian filter in two stages: the prediction stage takes into account the motion constraint provided by hospitability map and the estimation stage considers of all detection information that both the target is detected or not. Simulations show that the proposed approach provides a feasible solution to tracking maneuvering targets with intermittent measurements.