Cluster planning method for dense targets by remote sensing satellite swarm
Abstract
<p indent="0mm">In order to solve the problems of low efficiency, task conflicts, and resource waste in observing dense targets by remote sensing satellite swarm, this paper first proposes a regional clustering method, which integrates close point targets into regions and then divides them into strips according to satellite trajectories, so that the satellite can cover multiple targets in a single imaging. Subsequently, a mono scene clustering method is adopted for the remaining targets, which modified the payload pointing position to include more targets in the instantaneous field of view. The original target set is replaced by the cluster strips and points, and the points are mapped by gaze imaging and the strips are mapped by push scan imaging. Simulation examples show that clustering planning method can effectively reduce the number of missions, alleviate target observation conflicts, and reduce computational time. Moreover, the higher the target density, the more obvious the above effects become.</p>
