基于扩展信息滤波的跟踪传感器选择算法  

Tracking sensor selected algorithm based on extended information filter

作　　者：程佳林 张贞凯 CHENG Jia-lin1 , ZHANG Zhen- kai2(1. School of Electronics and information, Jiangsu University of Science and Technology, Zhenjiang 212003; 2. College of Electronics information and Communication, Huazhong University of Science and Technology, Wuhan 430074, Chin)

机构地区：[1]江苏科技大学电子与信息学院,江苏镇江212003 [2]华中科技大学电子信息与通信学院,湖北武汉430074

出　　处：《计算机工程与设计》2018年第8期2495-2499,共5页Computer Engineering and Design

基　　金：国家自然科学基金青年基金项目(61401179);江苏省属高校自然科学基金项目(14KJB510009)

摘　　要：针对目标跟踪时传感器系统资源有限问题,提出一种传感器组合自适应选择算法。从接收回波信号模型出发,建立基于扩展卡尔曼滤波的信息融合模型;通过设置期望协方差得到对应的期望信息增益,将各传感器的信息增益与期望信息增益进行比较;依次选择最优(即最接近期望信息增益)传感器组合对目标进行跟踪,直至满足跟踪精度要求。仿真结果表明,与现有的多传感器融合算法相比,所提算法能够自适应选择最优跟踪传感器,提高跟踪精度,节省系统资源。Focusing on the dynamic tracking problem in resource constrained sensor network,a sensor network adaptive selected algorithm was proposed.The echo signal model was taken into consideration to establish the information fusion model based on the extended Kalman filtering（EKF）.The expected information gain was obtained using the expected covariance,and each sensor’s information gain was compared with it.The best performance sensor was selected in turn to track the target until the tracking accuracy was satisfied.Simulation results show that the proposed algorithm can adaptively select tracking sensors,achieve the expected tracking accuracy and reduce the system resource.

关 键 词：目标跟踪 传感器选择 扩展信息滤波 期望信息增益 信息融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]