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基于扩展Kalman滤波的单领航者自主水下航行器协同导航判别式训练方法研究

杨少凡 余华兵 陈新华 孙长瑜

杨少凡, 余华兵, 陈新华, 孙长瑜. 基于扩展Kalman滤波的单领航者自主水下航行器协同导航判别式训练方法研究[J]. 电子与信息学报, 2015, 37(11): 2756-2761. doi: 10.11999/JEIT150036
引用本文: 杨少凡, 余华兵, 陈新华, 孙长瑜. 基于扩展Kalman滤波的单领航者自主水下航行器协同导航判别式训练方法研究[J]. 电子与信息学报, 2015, 37(11): 2756-2761. doi: 10.11999/JEIT150036
Yang Shao-fan, Yu Hua-bing, Chen Xin-hua, Sun Chang-yu. Discriminative Training of Kalman Filters Based Cooperative Navigation for Multiple Autonomous Underwater Vehicles with a Single Leader[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2756-2761. doi: 10.11999/JEIT150036
Citation: Yang Shao-fan, Yu Hua-bing, Chen Xin-hua, Sun Chang-yu. Discriminative Training of Kalman Filters Based Cooperative Navigation for Multiple Autonomous Underwater Vehicles with a Single Leader[J]. Journal of Electronics & Information Technology, 2015, 37(11): 2756-2761. doi: 10.11999/JEIT150036

基于扩展Kalman滤波的单领航者自主水下航行器协同导航判别式训练方法研究

doi: 10.11999/JEIT150036
基金项目: 

国家自然科学基金(61372180)

Discriminative Training of Kalman Filters Based Cooperative Navigation for Multiple Autonomous Underwater Vehicles with a Single Leader

Funds: 

The National Natural Science Foundation of China (61372180)

  • 摘要: 单领航者自主水下航行器(AUV)协同导航算法中,系统模型是非线性的,扩展Kalman滤波(EKF)是针对非线性系统的很有影响力的滤波算法,但是,EKF算法的性能严格依赖于一系列模型参数,而这些参数往往需要花费很大的代价来捕获,并且常需要人工调整。该文应用一种能自动学习Kalman滤波噪声协方差参数的方法,通过仿真分析,证明了该学习算法可以完全自主并且高效、准确地输出Kalman滤波噪声参数,进一步提高了单领航者AUV协同导航系统的导航精度。
  • Paull L, Saeedi S, Seto M, et al.. AUV navigation and localization: A review[J]. IEEE Journal of Oceanic Engineering, 2014, 39(4): 131-149.
    Liu Ming-yong, Li Hong, and Liu Kun. Geomagnetic navigation of AUV without a priori magnetic map[C]. MTS/ IEEE OCEANS, Taipei, 2014: 1-5.
    刘明雍. 水下航行器协同导航技术[M]. 北京: 国防工业出版社, 2014: 1-117.
    Liu Ming-yong. Cooperative Navigation Technology for Underwater Vehicles[M]. Beijing: National Defence Industry Press, 2014: 1-117.
    Kalman R. A new approach to linear filtering and prediction problems[J]. Transactions of the ASME-Journal of Basic Engineering, 1960, 82(Series D): 35-45.
    Abbeel P, Coates A, Montemerlo M, et al.. Discriminative training of Kalman filters[C]. Robotic: Science and Systems, Cambridge, 2005: 289-296.
    Zhang Li-chuan, Xu De-min, Liu Ming-yong, et al.. Cooperative navigation and localization for multiple UUVs [J]. Journal of Marine Science and Application, 2009, 8(3): 216-221.
    Fallon M, Papadopoulos G, Lenorad J, et al.. Cooperative AUV navigation using a single maneuvering surface craft[J]. The International Journal of Robotics Research, 2011, 29(12): 1461-1474.
    李闻白, 刘明雍, 李虎雄,等. 基于单领航者相对位置测量的多AUV协同导航系统定位性能分析[J]. 自动化学报, 2011, 37(6): 724-736.
    Li Wen-bai, Liu Ming-yong, Li Hu-xiong, et al.. Localization performance analysis of cooperative navigation system for multiple AUVs based on relative position measurements with a single leader[J]. Acta Automatica Sinica, 2011, 37(6): 724-736.
    Liu Ming-yong, Li Wen-bai, Mu Bing-xian, et al.. Cooperative navigation for multiple AUVs based on relative range measurements with a single leader[C]. IEEE International Conference on Intelligent Computing and Intelligent Systems, Xiamen, 2010: 762-766.
    Liu Jian, Xu De-min, Zhang Fu-bin, et al.. Research on cooperative navigation for multiple UUVs[C]. International Symposium on Instrumentation Measurement, Sensor Network and Automation, Sanya, 2012: 248-251.
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    Roweis S and Ghahramani Z. A unifying review of linear Gaussian models[J]. MIT Press Journals, 1999, 11(2): 305-345.
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  • 被引次数: 0
出版历程
  • 收稿日期:  2015-01-08
  • 修回日期:  2015-06-02
  • 刊出日期:  2015-11-19

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