基于传感器个数加权的分布式多传感器信息融合  

Distributed multi-sensor information fusion based on weighted number of sensors

作　　者：刘建锋 LIU Jian-feng(Key Laboratory of Radar Imaging and Microwave Photonics,Ministry of Education,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学,雷达成像与微波光子学教育部重点实验室

出　　处：《信息技术》2020年第2期22-27,共6页Information Technology

基　　金：航空科学基金(2017ZC52036,20172752019)

摘　　要：多传感器信息融合在跟踪多个目标和隐身小目标时有着不可替代的作用。为解决集中式扩维和分布式多传感器信息融合中普遍存在的计算量大、难以实时应用的问题,文中提出一种使用传感器网络中参与融合传感器个数加权的数据融合方法。文中通过分析集中式扩维融合、基于协方差分布式加权融合方法,在不考虑传感器间互协方差的条件下,提出使用传感器个数进行统计加权融合思路。仿真结果表明,文中提出的方法相较于单传感器的位置估计精度提高了16.67%,速度估计精度提高了7.69%,获得了和“Hu等人的算法”相近估计性能,优于“Pao等人的方案”性能,并且缩短了运行时间,这说明文中提出的方法具有较好的应用性。Multi-sensor information fusion plays an irreplaceable role in tracking multiple targets and small stealthy targets.In order to solve the problem of large amount of computation and difficult real-time application in centralized extended-dimension and distributed multi-sensor information fusion,a data fusion method using weighted number of sensors in sensor networks is proposed.By analyzing the centralized extended dimension fusion and distributed weighted fusion based on covariance,a statistical weighted fusion method using the number of sensors is proposed without considering the cross-covariance between sensors.The simulation results show that the proposed method improves the position estimation accuracy by 16.67%and the speed estimation accuracy by 7.69%compared with the single sensor.The performance of the proposed method is similar to that of Hu et al.’s algorithm,which is better than that of Pao et al.’s scheme,and has a shorter running time,which shows that the method proposed in this paper has good applicability.

关 键 词：多传感器信息融合 统计加权 凸组合优化 协方差交叉 

分 类 号：TN953[电子电信—信号与信息处理]