AUV组合导航系统中<em>H<sub>∞</sub></em>滤波技术

段世梅; 康凤举; 王彦恺; 黄永华

doi:10.11993/j.issn.1673-1948.2009.01.004

AUV组合导航系统中H_∞滤波技术

doi: 10.11993/j.issn.1673-1948.2009.01.004

西北工业大学航海学院,陕西西安 710072

基金项目: 国防科技重点实验室基金资助项目

详细信息

作者简介:
段世梅(1984- )，女,在读硕士，研究方向为制导、控制与仿真.

中图分类号: TP391.9
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- 被引次数: 0
出版历程
- 收稿日期: 2008-01-24
- 修回日期: 2008-03-03
- 刊出日期: 2009-02-28

H_∞ Filter Technology in Integrated Navigation System of AUV

College of Marine Engineering, Northwestern Polytechnical University, Xi′an 710072,China

摘要

摘要: 为了提高自主水下航行器（AUV）组合导航系统精度，选择了捷联式惯性导航系统（SINS) 、多普勒速度声纳（DVS）以及地形匹配导航系统（TAN）作为AUV组合导航系统导航传感器，建立了AUV组合导航系统的状态模型和导航传感器观测模型，运用了一种基于径向基函数(RBF)神经网络进行H_∞滤波信息分配的信息融合方法,并进行了计算机软件仿真。仿真结果表明，在有色噪声情况下，AUV组合导航系统的导航姿态、速度和位置精度得到了提高，有效地克服了传统滤波容易发散的缺点，提高了AUV组合导航系统的容错性能和导航精度。
- 自主水下航行器（AUV) /
- 捷联式惯性导航系统（SINS) /
- 多普勒速度声纳（DVS) /
- 地形匹配导航系统（TAN) /
- H_∞滤波 /
- 组合导航系统
Abstract: To improve the autonomous underwater vehicle (AUV) navigation accuracy, strap-down inertial navigation system (SINS) , Doppler velocity sonar (DVS) and terrain aided navigation (TAN) were adopted in the AUV integrated navigation system. Mathematical models of the AUV integrated navigation system and an observation model of the chosen navigation sensors were built according to the system simulation data. An improved filter based on radial basis function (RBF) neural network for adjusting the information sharing factors was designed and implemented in the AUV integrated navigation system. Simulation results show that the navigation accuracy is improved obviously with the specified sensors andH_∞filter in the case of colored noise. The novel integrated navigation system can effectively suppress the divergence of the filter, improve the fault tolerance ability, and greatly raise the navigation accuracy.
- autonomous underwater vehicle(AUV) /
- strap-down inertial navigation system (SINS) /
- Doppler velocity sonar (DVS) /
- terrain aided navigation (TAN) /
- H_∞ filter /
- integrated navigation system

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参考文献(6)

[1]	Broatch S A, Henley A J. An Integrated Navigation System Manager Using Federated Kalman Filtering[R].2005 International Conference on Control and Automation, 2005: 1103-1107.
[2]	张福斌，高剑，崔荣鑫.一种水下航行器组合导航系统研究[J].鱼雷技术，2007,15(1):19-2.
[3]	曹杰，刘繁明，陈勤，高伟.AUV中SINS/DVL组合导航技术研究[J].中国航海,2004(2):1000-4653.
[4]	付梦印，邓志红，张继伟.Kalman滤波理论及其在导航系统中的应用[M].北京:科学出版社，2003.
[5]	秦政,李娟,王奎民,刘光军.自主式水下潜器导航仿真系统研究[J].系统仿真学报.2006,18(9):2465-2468.
[6]	Xiao K, Fang S J, Pang Y J. Strong Tracking Adaptive Kalman Filters for Underwater Vehicle Dead Reckoning[J].Journal of Marine Science and Application,2007,6(2):19-24.