通信受限下分布式多传感器协同跟踪算法

Distributed Multi-sensor Target Collaborative Tracking Algorithm under Communication Constraints

在分布式多传感器目标跟踪系统中,由于局部融合中心(LFC)的物理限制(如:有限的频率信道、处理器容量有限等),只能接收有限个传感器的传送数据。此外,信息传输的方式也将影响传感网的使用寿命,因此,研究了通信受限下的分布式多传感器目标协同跟踪问题。首先对监视区内分布的传感器进行聚类分簇形成若干个子网,接着从通信能耗的角度出发,对传感器采集信息的传递路径进行最优路径规划;进而对子网局部状态进行估计,在子网信息融合中,分别采用最大距离和、最大化信息增量两种准则进行最佳传感器选择,最后通过各子网全局航迹融合实现分布式多传感器协同跟踪。仿真验证了算法的有效性。

In a distributed multi-sensor target tracking system,the physical limitation of the local fusion center（LFC）（limited frequency channel,limited processor capacity） is considered,which can only receive the transmission data of a finite number of sensors.In addition,the way of information transmission will affect the service life of the sensor network,so this paper studies the distributed multi-sensor target tracking problem under communication constraints. In this paper,the distributed sensors in the monitoring area are firstly combined to a number of sub-networks,and then the optimal transmission path of sensor data is determined by minimizing the communication consumption costs.Moreover the local state of each sub-network is estimated. In the local fusion center,the sensor is selected based on the maximum distance and the maximum information increment. Finally the multisensor collaborative tracking is implemented by the global track fusion. Simulation results show the effectiveness of the proposed algorithm.