Research on the algorithm of multi-autonomous underwater vehicles navigation and localization based on the Extended Kalman Filter

机译：基于扩展卡尔曼滤波器的多自动水下车辆导航和定位算法研究

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The technology of navigation and localization for Multi-Autonomous Underwater Vehicles (AUVs) is an important way to solve the problem of complex operation environment. This paper addresses the problem of Multi-AUVs cooperative navigation and localization, based on the Leader-Fellow form. Then, Extended Kalman Filter (EKF) algorithm is proposed to solve this problem. A navigation model of the slave AUV is established, using the kinematic equations of the slave AUV and the measurement equations based on the distance between the master AUV and the slave AUV. The proposed algorithm-EKF proves to be effective if applied to the nonlinear model and avoids the filtering divergence problem by linearizing the nonlinear equations. The simulation shows the feasibility of the EKF algorithm for Multi-AUVs cooperative navigation and localization and achieves a satisfying accuracy improvement compared to the conventional Kalman Filter (KF) algorithm.

机译：多自治水下车辆（AUV）的导航和定位技术是解决复杂操作环境问题的重要途径。本文根据领导者 - 同伴，解决了多AUVS协作导航和本地化问题。然后，建议扩展卡尔曼滤波器（EKF）算法来解决这个问题。基于主AUV和从AUV之间的距离，使用从AUV和测量方程的运动学方程来建立从AUV的导航模型。如果应用于非线性模型，所提出的算法-EKF证明是有效的，并通过线性化非线性方程来避免滤波发散问题。该模拟显示了与传统的卡尔曼滤波器（KF）算法相比，实现了多AUVS协作导航和定位的EKF算法的可行性，并实现了满足的准确性改进。

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《IEEE International Conference on Mechatronics and Automation》|2016年|1 v.|共6页
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Juan Li; Juan Zhang;
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中图分类自动化技术及设备;
关键词
Navigation; Mathematical model; Underwater vehicles; Kalman filters; Estimation; Time measurement;

机译：导航;数学模型;水下车辆;卡尔曼过滤器;估计;时间测量;

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专利

1. An unscented Kalman filter based navigation algorithm for autonomous underwater vehicles [J] . Allotta B., Caiti A., Chisci L., Mechatronics: The Science of Intelligent Machines . 2016,第Null期

机译：基于无味卡尔曼滤波器的水下航行器导航算法
2. Study of the Algorithm of Backtracking Decoupling and Adaptive Extended Kalman Filter Based on the Quaternion Expanded to the State Variable for Underwater Glider Navigation [J] . Caiping Lv, Haoqian Huang, Xiyuan Chen, Sensors . 2014,第12期

机译：基于四元数扩展到状态变量的水下滑翔机导航回溯解耦和自适应扩展卡尔曼滤波算法研究
3. A fuzzy Kalman filter optimized using a multi-objective genetic algorithm for enhanced autonomous underwater vehicle navigation [J] . D Loebis, R Sutton, J Chudley Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment . 2004,第1期

机译：使用多目标遗传算法优化的模糊卡尔曼滤波器，用于增强型自主水下航行器导航
4. Research on the algorithm of multi-autonomous underwater vehicles navigation and localization based on the Extended Kalman Filter [C] . Juan Li, Juan Zhang IEEE International Conference on Mechatronics and Automation . 2016

机译：基于扩展卡尔曼滤波的多水下机器人导航定位算法研究
5. Using extended Kalman filtering (EKF) to fuse GPS and inertial navigation systems (INS) for land vehicle control. [D] . Zhang, Hao. 2004

机译：使用扩展的卡尔曼滤波（EKF）融合GPS和惯性导航系统（INS）进行陆地车辆控制。
6. Study of the Algorithm of Backtracking Decoupling and Adaptive Extended Kalman Filter Based on the Quaternion Expanded to the State Variable for Underwater Glider Navigation [O] . Haoqian Huang, Xiyuan Chen, Zhikai Zhou, 2014

机译：基于四元数扩展到状态变量的水下滑翔机导航回溯解耦和自适应扩展卡尔曼滤波算法研究
7. Study of the Algorithm of Backtracking Decoupling and Adaptive Extended Kalman Filter Based on the Quaternion Expanded to the State Variable for Underwater Glider Navigation [O] . Haoqian Huang, Xiyuan Chen, Zhikai Zhou, 2014

机译：基于四元数扩展到水下滑翔机导航状态变量的回溯解耦和自适应扩展卡尔曼滤波算法研究

Research on the algorithm of multi-autonomous underwater vehicles navigation and localization based on the Extended Kalman Filter

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