基于信息增量的多被动传感器资源分配算法

针对多被动传感器多目标跟踪中的传感器资源分配问题进行研究。讨论了多被动传感器跟踪误差的克拉美-罗下限，在此基础上分析了多被动传感器系统跟踪误差的几何分布。为解决多目标跟踪中的传感器资源分配问题，通过先验信息熵与后验信息熵之间的差值获得信息增量；在此基础上针对多被动传感器系统的特点构建最优化分配模型，将被动传感器组合在不同时刻动态地分配给不同目标。仿真实验表明，与不考虑资源分配的固定跟踪模式相比，该方法能够高效合理地利用有限资源，并且使多被动传感器多目标跟踪系统的整体跟踪性能得到提高。

Multi-passive sensors resource allocation algorithm based on information gain

In the domain of multi-target tracking with multi-passive sensors,the problem of sensor resource allocation is researched.The Cramer-Rao lower bound of tracking error of multi-passive sensors is discussed,and the geometrical of tracking error(GDTE) is analysed.In order to solve the problem of sensors resource allocation in multi-target tracking,the information gain is achieved through the difference of prior information entropy and posterior information entropy.For the characteristics of the multi-passive sensors system,an optimization model is established.At different times dissimilar sensor combinations are dynamically allocated to different targets.Simulation results show that compared with the fixed schedule in which the resource allocation is not considered,the proposed method can efficiently utilize the limited resource,and the whole tracking performance of multi-passive sensors and multi-target tracking system is improved.