基于多模型的低轨星座多目标跟踪传感器资源调度

针对低轨星座多目标持续跟踪传感器资源调度问题,首先将目标跟踪任务划分为高精度任务集合和低精度任务集合,并分析了跟踪任务状态转移过程;然后,为两任务集合分别建立了基于动态优先级的优化调度模型,提出了一种基于多模型的实时传感器调度算法。不同场景下仿真实验表明,所提算法较之以跟踪精度为优化目标和以跟踪精度为门限约束的方法具有更强的适用性,尤其对于目标分布较为集中的情况,其目标丢失率大大降低,尽管个别目标的跟踪误差略有增大。

Multi-object Tracking Sensor Scheduling for Low Earth Orbit Constellation Based on Multi-model

To deal with the problem of sensor resource scheduling for continual multi-object tracking with low earth orbit constellation, the object tracking tasks are first classified into two sets, i.e., the higher precision task set and the lower precision task set, and their state transition procedures are analyzed. Then, a sensor scheduling model for each task set is established based on the dynamic priority theory. Furthermore, a novel real-time sensor scheduling algorithm based on a multi-model is proposed. Simulations executed in diverse scenarios indicate that the applicability of the proposed algorithm exceeds that of the traditional methods which consider the dilution of precision as the optimal objective or threshold constraint. This is especially true in the case of multi-object scenarios of centralized distribution. The drop-out ratio of the proposed method is greatly reduced as compared with that of the traditional methods, although a few objects show slightly larger tracking errors.