%0 Journal Article
%T Small Autonomous Underwater Vehicle Navigation System Based onAdaptive UKF Algorithm<br>基于自适应UKF算法的小型水下机器人导航系统
%A SUN Yao
%A ZHANG Qiang
%A WAN Lei
%A <br>孙尧
%A 张强
%A 万磊
%J 自动化学报
%D 2011
%I 
%X Ocean current disturbance and attitude, heading errors can cause uncertain navigation system model error. To solve the above problem, an adaptive unscented Kalman filter (AUKF) with model error is designed for a small autonomous underwater vehicle's (SAUV) dead reckoning (DR) navigation system. Firstly, three-dimensional motion of SAUV continuous time model is designed. Then, the proposed AUKF algorithm is deduced according to maximum a posterior (MAP) theory. Finally, simulation results show that the algorithm can overcome the model error caused by disturbance currents and attitude, and heading errors. Compared with the conventional UKF algorithm, the filter precision of the SAUV's DR navigation system in complex sea state is improved a lot by adopting the proposed algorithm.
%K Adaptive unscented Kalman filter (AUKF)
%K small autonomous underwater vehicle (SAUV)
%K dead reckoning navigation system
%K nonlinear
%K maximum a posterior (MAP) estimation<br>自适应无迹卡尔曼滤波器
%K 小型水下机器人
%K 推位导航系统
%K 非线性
%K 极大后验估计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=903143EDEB2353B892CBE3EA4BF5BADA&yid=9377ED8094509821&vid=42425781F0B1C26E&iid=38B194292C032A66&sid=556C1A86E372B606&eid=A5111BA190517959&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=0