[1] Li Qinghua, Chen Xiyuan, Xu Yuan, et al. Distributed H∞ fusion filter designfor INS/WSN integrated positioning system [J]. Journal of Southeast University (English Edition), 2012, 28 (2): 164-168. [doi:10.3969/j.issn.1003-7985.2012.02.006]

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Distributed H_∞ fusion filter designfor 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

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

28

Issue:

2012 2

Page:

164-168

Research Field:

Electromagnetic Field and Microwave Technology

Publishing date:

2012-06-30

Info

Title:

Distributed H_∞ fusion filter designfor 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

Author(s):

Li Qinghua^{1, 2}, Chen Xiyuan^{1, 3}, Xu Yuan^{1, 3}

¹School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
² School of Electrical Engineering and Automation, Shandong Polytechnic University, Jinan 250353, China
³ Key Laboratory of

李庆华^{1, 2}, 陈熙源^{1, 3}, 徐元^{1, 3}

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

Keywords:

inertial navigation system;  wireless sensor network;  H_∞ filter;  distributed fusion

惯性导航系统;  无线传感器网络;  H_∞滤波器;  分布融合

PACS:

TN967.3

DOI:

10.3969/j.issn.1003-7985.2012.02.006

Abstract:

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.

References:

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Memo

Memo:

Biographies: Li Qinghua(1977—), male, doctor, associate professor; Chen Xiyuan(corresponding author), male, doctor, professor, chxiyuan@seu.edu.cn.
Foundation items: 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).
Citation: Li Qinghua, Chen Xiyuan, Xu Yuan. Distributed H_∞ fusion filter design for INS/WSN integrated positioning system[J].Journal of Southeast University(English Edition), 2012, 28(2):164-168.[doi:10.3969/j.issn.1003-7985.2012.02.006]

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