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AUV dead-reckoning navigation based on neural network using a single accelerometer
Xie, Yanxin; Liu J(刘军); Hu CQ(胡成全); Cui JH(崔军红); Xu HL(徐红丽)
作者部门海洋信息技术装备中心
会议名称11th ACM International Conference on Underwater Networks and Systems, WUWNet 2016
会议日期October 24-26, 2016
会议地点Shanghai, China
会议主办者ACM Special Interest Group on Mobility of Systems, Users, Data, and Computing (SIGMOBILE); Acoustical Society of China (ASC); Association for Computing Machinery (ACM)
会议录名称WUWNet 2016 - 11th ACM International Conference on Underwater Networks and Systems
出版者ACM
出版地New York
2016
页码1-5
收录类别EI
EI收录号20165003114036
产权排序1
ISBN号978-1-4503-4637-5
关键词Dead-reckoning Neural Networks Accelerometer
摘要The accuracy of the Autonomous Underwater Vehicles (AUVs) navigation system determines whether they can safely operate and return. Traditional Dead-reckoning (DR) relies on the inertial sensors such as gyroscope and accelerometer. A major challenge for DR navigation is from measurement error of the inertial sensors (gyroscope, accelerometer, etc.), especially when the AUV is near or at the ocean surface. The AUV's motion is affected by ocean waves, and its pitch angle changes rapidly with the waves. This rapid change and the measurement errors will cause great noise to the direction measured by gyroscopes, and then lead to a large error to the DR navigation. To address this problem, a novel DR method based on neural network (DR-N) is proposed to explore the time-varying relationship between acceleration measurement and orientation measurement, which leverages acoustic localization and neural network estimate timely pitch angle through the explored time-varying relationship. This method enables AUV's DR navigation with a single acceleration, without relying on both acceleration and gyroscope. Most importantly, we can improve the accuracy of AUV navigation through avoiding DR errors caused by gyroscope noise at the sea surface. Simulations show DR-N significantly improves navigation accuracy.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/20082
专题海洋信息技术装备中心
通讯作者Liu J(刘军)
作者单位1.State Key Laboratory of Robotics, CAS No. 114 Nanta Street, Shenhe District, Shenyang, China
2.College of Computer Science and Technology, Jilin University, Changchun, China
3.Underwater Sensor Network Lab., University of Connecticut, Storrs, CT 06269, United States
4.Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
推荐引用方式
GB/T 7714
Xie, Yanxin,Liu J,Hu CQ,et al. AUV dead-reckoning navigation based on neural network using a single accelerometer[C]//ACM Special Interest Group on Mobility of Systems, Users, Data, and Computing (SIGMOBILE); Acoustical Society of China (ASC); Association for Computing Machinery (ACM). New York:ACM,2016:1-5.
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