AUV dead-reckoning navigation based on neural network using a single accelerometer

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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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