[1] Xu Yuan, Chen Xiyuan,. Tightly-coupled model for INS/WSN integrated navigationbased on Kalman filter [J]. Journal of Southeast University (English Edition), 2011, 27 (4): 384-387. [doi:10.3969/j.issn.1003-7985.2011.04.008]

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Tightly-coupled model for INS/WSN integrated navigationbased on Kalman filter()

基于Kalman滤波器的INS/WSN紧组合导航系统模型

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

Volumn:

27

Issue:

2011 4

Page:

384-387

Research Field:

Electromagnetic Field and Microwave Technology

Publishing date:

2011-12-31

Info

Title:

Tightly-coupled model for INS/WSN integrated navigationbased on Kalman filter

基于Kalman滤波器的INS/WSN紧组合导航系统模型

Author(s):

Xu Yuan, Chen Xiyuan

School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology of Ministry of Education, Southeast University, Nanjing 210096, China

徐元, 陈熙源

东南大学仪器科学与工程学院, 南京 210096; 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(INS);  wireless sensor network(WSN);  tightly-coupled integration;  Kalman filter

惯性导航系统;  无线传感器网络;  紧组合;  卡尔曼滤波

PACS:

TN967.3

DOI:

10.3969/j.issn.1003-7985.2011.04.008

Abstract:

Aiming at the problem of poor observability of measurement information in the loosely-coupled integration of the inertial navigation system(INS)and the wireless sensor network(WSN), this paper presents a tightly-coupled integration based on the Kalman filter(KF). When the WSN is available, the difference between the distances from the blind node(BN)to the reference nodes(RNs)measured by the INS and those measured by the WSN are used as measurement information for the KF due to its better observability and independence, which can effectively improve the accuracy of the KF. Simulations show that the proposed approach reduces the mean error of the position by about 50% compared with loosely-coupled integration, while the mean error of the velocity is a little higher than that of loosely-coupled integration.

在基于惯性导航系统和无线传感器网络的组合导航系统中, 为了解决传统导航信息松组合方法中测量信息可观性较差的问题, 提出了一种基于卡尔曼滤波器的导航信息紧组合模型.当无线传感器网络的信号可用时, 组合导航系统将惯性导航系统测量得到的未知节点与已知节点的距离与无线传感器网络测量得到的距离作差, 差值作为卡尔曼滤波器的测量信息.由于新测量信息具有更好的可观性和独立性, 该方法有效地提高了卡尔曼滤波器的准确度.仿真结果显示, 提出的方法平均位置误差比松组合方法降低50%左右, 但平均速度误差却略高于松组合方式.

References:

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Memo

Memo:

Biographies: Xu Yuan(1985—), male, graduate; 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 of China(No.20110092110039), the Aviation Science Foundation(No.20090869008), the Six Peak Talents Foundation in Jiangsu Province(No.2008143), Program of Scientific Innovation Research of College Graduate in Jiangsu Province(No.CXLX_0101).
Citation: Xu Yuan, Chen Xiyuan.Tightly-coupled model for INS/WSN integrated navigation based on Kalman filter[J].Journal of Southeast University(English Edition), 2011, 27(4):384-387.[doi:10.3969/j.issn.1003-7985.2011.04.008]

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