LI Zengke, WANG Jian, GAO Jingxiang, TAN Xinglong. A Method to Prevent GPS / INS Integrated Navigation Filtering Divergence Based on SVM[J]. Geomatics and Information Science of Wuhan University, 2013, 38(10): 1216-1220.
Citation: LI Zengke, WANG Jian, GAO Jingxiang, TAN Xinglong. A Method to Prevent GPS / INS Integrated Navigation Filtering Divergence Based on SVM[J]. Geomatics and Information Science of Wuhan University, 2013, 38(10): 1216-1220.

A Method to Prevent GPS / INS Integrated Navigation Filtering Divergence Based on SVM

Funds: 国家自然科学基金青年基金资助项目(40904004);国家自然科学基金资助项目(41074010),江苏省高校优势学科建设工程资助项目;江苏省普通高校研究生科研创新计划资助项目(CXZZ12_0939)
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  • Received Date: June 11, 2013
  • Revised Date: October 04, 2013
  • Published Date: October 04, 2013
  • A GPS / INS integrated navigation model is introduced in order to verify the naviga-tion ability in the condition of low GPS signal update frequency. The GPS signal break period were chosen 5s, 10sand 15sduring the vehicle motion, which has demonstrated that long signal interruption interval (above 10s) will lead to the Kalman filtering divergence after GPS signal reconstruction. Considering that the integrated navigation model has favorable effect in high GPS signal update frequency, a new method is proposed to prevent the filtering divergence. The approach adopted extensively is called support vector machine (S VM) inter-polating the GPS signal based on vehicle movement discipline. These findings of the research have led the author to the conclusion that SVM is able to increase the GPS signal update fre-quency to prevent the filtering divergence caused by long GPS signal interruption interval and strengthen the navigation accuracy.
  • [1]
    王坚,刘超,高井祥,许长辉. 基于抗差EKF的GNSS/INS紧组合算法研究[J]. 武汉大学学报(信息科学版). 2011(05)[2] 吴富梅,杨元喜,崔先强. 利用部分状态不符值构造的自适应因子在GPS/INS紧组合导航中的应用[J]. 武汉大学学报(信息科学版). 2010(02)[3] 高为广,杨元喜,崔先强,张双成. IMU/GPS组合导航系统自适应Kalman滤波算法[J]. 武汉大学学报(信息科学版). 2006(05)[4] 杨元喜,何海波,徐天河. 论动态自适应滤波[J]. 测绘学报. 2001(04)[5] Yanrui Geng,Jinling Wang. Adaptive estimation of multiple fading factors in Kalman filter for navigation applications[J]. GPS Solutions . 2008 (4)
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