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Alternative TitleSVR assisted SINS-DVL underwater robot integrated navigation method
魏奥博1,2,3; 郑荣1,2
Source Publication舰船科学技术
Contribution Rank1
Funding Organization中国科学院装备预研联合基金资助项目(6141A01061601)
KeywordSVR SINS-DVL 组合导航 DVL数据无效


Other Abstract

DVL is more and more widely used in underwater navigation system. When the seabed environment changes, the data refresh frequency of DVL is unstable and the data is invalid. In order to improve the reliability of navigation, this paper proposes a SVR regression method of variable training set to predict DVL data. The training set size is adjusted according to the change of velocity rate and acceleration rate of underwater robot. Taking the east and north velocity of SINS as input, DVL's east and north velocity as output, the model is trained. We select the appropriate predictive data output frequency that relys on the data out frequency of SINS. It is found that SINS/DVL integrated navigation precision is effectively improved through simulation. When the DVL data is invalid, the error is effectively suppressed and the stability of the navigation system is improved.

Document Type期刊论文
Corresponding Author魏奥博
Recommended Citation
GB/T 7714
魏奥博,郑荣. SVR辅助SINS-DVL的水下机器人组合导航方法[J]. 舰船科学技术,2020,42(1):161-167.
APA 魏奥博,&郑荣.(2020).SVR辅助SINS-DVL的水下机器人组合导航方法.舰船科学技术,42(1),161-167.
MLA 魏奥博,et al."SVR辅助SINS-DVL的水下机器人组合导航方法".舰船科学技术 42.1(2020):161-167.
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