Distributed H_∞ fusion filter design for INS/WSN integrated positioning system  

面向INS/WSN组合定位的分布式H_∞融合滤波器设计(英文)

作　　者：李庆华[1,2] 陈熙源[1,3] 徐元[1,3] 

机构地区：[1]东南大学仪器科学与工程学院,南京210096 [2]山东轻工业学院电气工程与自动化学院,济南250353 [3]东南大学微惯性仪表与先进导航技术教育部重点实验室,南京210096

出　　处：《Journal of Southeast University(English Edition)》2012年第2期164-168,共5页东南大学学报（英文版）

基　　金：The National Basic Research Program of China (973 Program) (No. 2009CB724002);the National Natural Science Foundation of China (No. 50975049);the Specialized Research Fund for the Doctoral Program of Higher Education (No. 20110092110039);the Program for Special Talents in Six Fields of Jiangsu Province (No.2008143);the Program Sponsored for Scientific Innovation Research of College Graduates in Jiangsu Province,China (No. CXLX_0101)

摘　　要：In order to keep stable navigation accuracy when the blind node （BN） moves between two adjacent clusters, a distributed fusion method for the integration of the inertial navigation system （INS） and the wireless sensor network （WSN） based on H∞ filtering is proposed. Since the process and measurement noise in the integration system are bounded and their statistical characteristics are unknown, the H∞ filter is used to fuse the information measured from local estimators in the proposed method. Meanwhile, the filter can yield the optimal state estimate according to certain information fusion criteria. Simulation results show that compared with the federal Kalman solution, the proposed method can reduce the mean error of position by about 45% and the mean error of velocity by about 85 %.为了保持未知节点在 2 个相邻簇之间移动时导航精度的稳定,提出了一种基于 H∞滤波的惯性导航系统和无线传感器网络组合导航分布式融合方法. 由于组合系统的过程和测量噪声具有未知的但能量有界的统计特性,因此在提出的方法中,用 H∞滤波器来融合局部估计测量的信息. 该滤波器能够根据一定的信息融合准则产生最佳的状态估计. 仿真结果显示: 与联邦卡尔曼方法相比,提出的方法降低了 45%的平均位置误差和 85%的平均速度误差.

关 键 词：inertial navigation system wireless sensor network H∞ filter distributed fusion 

分 类 号：TN967.3[电子电信—信号与信息处理]