基于分支剔除的低轨星座实时传感器调度算法

针对低轨星座目标连续跟踪的传感器资源调度问题，通过对调度约束因素的分析，提取跟踪精度、资源松弛度和资源分配均衡因子三个优化参数，建立了传感器实时调度模型；并建立长时调度决策树，将标准代价搜索方法和分支剔除技术相结合，提出了一种基于分支剔除的实时传感器调度算法。仿真实验表明，标准代价搜索和分支剔除技术的引入明显降低了调度算法的运算量，尤其对于多目标和大步长的情况，且调度传感器跟踪目标的误差略小于短时调度方法。

Real-time sensor scheduling algorithm in LEO constellation based on pruning

To deal with the sensor resource scheduling in continual object tracking of low earth orbit (LEO) constellation, a real-time sensor scheduling model is established based on three parameters, i.e., tracking precision, resource slack, and equilibrium factor, according to an analysis of the sensor scheduling constraint factors. Furthermore, a non-myopic scheduling decision tree is developed, and combining the uniform cost search and pruning technology, a novel real-time sensor scheduling algorithm based on pruning is proposed. The simulation results indicate that the calculation load of the sensor scheduling algorithm is reduced obviously, especially to the cases of multi-target and longer step length, moreover, the tracking error of the proposed method is slightly lower than the myopic one.