稳健性(进化)
离群值
惯性导航系统
计算机科学
控制理论(社会学)
惯性测量装置
水下
导航系统
实时计算
滤波器(信号处理)
计算机视觉
人工智能
惯性参考系
地质学
量子力学
基因
海洋学
物理
生物化学
化学
控制(管理)
作者
Shede Liu,Tao Zhang,Jiayu Zhang,Yeyu Zhu
出处
期刊:IEEE Transactions on Instrumentation and Measurement
[Institute of Electrical and Electronics Engineers]
日期:2021-01-01
卷期号:70: 1-11
被引量:13
标识
DOI:10.1109/tim.2021.3106118
摘要
The integrated navigation of strap-down inertial navigation system (SINS) and Doppler velocity logs (DVL) has the common application in the positioning of autonomous underwater vehicle (AUV). However, DVL may be interrupted for a short time when part of the beam cannot receive the reflected signal and DVL measurement information is easily affected by underwater complex environment and contains outliers. To solve the above problems, a Doppler shifts aided coupled method of SINS/DVL integrated navigation with pare of DVL beam measurements outages based on dual adaptive factors is proposed. In this paper, a tightly coupled approach for SINS/DVL based on Doppler shifts is proposed to solve the short-term failure problem caused by the lack of part measurement in DVL. Then a chi-square detection aided dual factors adaptive filter is used to suppress the outliers. The dual factors are used to adjust the influence of imprecise information of dynamic model and observation model error. The chi-square detection is used to judge the outliers of measurements and the result of judgment is regarded as the precondition of factor selection. In order to verify the robustness of the proposed algorithm to outliers, simulation and Yangtze River experiments are carried out. The results of simulation and river experiments indicate that the tightly coupled approach obtain higher accuracy compared by the loosely coupled model and the proposed adaptive filter can effectively suppress the outliers. The method proposed in this paper can achieve greater robustness in AUV underwater complex environment.
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