通信受限时传感器管理方法研究  

A sensor management algorithm used for limited communication

作　　者：张华睿[1] 杨宏文[1] 胡卫东[1] 郁文贤[1] 

机构地区：[1]国防科学技术大学ATR重点实验室,长沙410073

出　　处：《电光与控制》2007年第4期70-73,81,共5页Electronics Optics & Control

基　　金：国防预研基金资助项目(41306030102)

摘　　要：在通信受限的情况下,如何进行传感器的管理以满足多目标的跟踪需求,优化完成跟踪任务。针对这一问题,对通信受限这种情形进行了描述,提出了数据获取概率的概念;利用扩展卡尔曼滤波和序贯卡尔曼滤波推出了序贯扩展卡尔曼滤波算法;结合信息论传感器管理方法和协方差控制传感器管理方法的优缺点提出了一种新的传感器分配准则。对比仿真实验表明,这种新的传感器管理方法能对传感器进行良好的管理,减小通信受限所带来的干扰;相比传统的传感器管理方法,传感器分配更为合理。When communication is limited, how to allocate sensors to meet multi-target tracking requirements and optimize the achieving of tracking tasks？ The authors analyzed the situation of limited communication, proposed a concept of＇observation acquisition probability＂, and put forward a sequential Extended Kalman Filter （EKF） algorithm based on EKF and sequential Kalman filter. Moreover, a new sensor assignment rule was presented by combining the two sensor management algorithms together, i.e., the algorithm respectively based and on covariance control. Simulation results show that the new method can allocate sensors well, reduce the influence of limited communication, and is more reasonable than traditional algorithms.

关 键 词：传感器管理 目标跟踪 军事通信 数据融合 序贯扩展卡尔曼滤波 

分 类 号：V271.4[航空宇航科学与技术—飞行器设计]