Kalman tracking of ocean current field based on distributed sensor network

Ying Zhang, Jiamin Huang, Hangfang Zhao, Wen Xu
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引用次数: 2

Abstract

Acoustic mapping of ocean currents with Distributed Networked Underwater Sensors (DNUS) system is an effective and energy-saving technique for monitoring oceanographic environments. Unlike the common acoustic tomography methods, this new approach can locally reconstruct ocean currents using data between neighboring sensors. Considering that ocean currents are highly correlated during a short time interval, this paper develops a Kalman filter based tracking approach to improve the DNUS-based ocean current estimation. A 2-D ocean model is used to generate synthetic observational data. The simulation results show that, with the information of the previous ocean current estimates introduced, the proposed method can outperform the traditional current mapping method with DNUS-type system.
基于分布式传感器网络的海流场卡尔曼跟踪
分布式网络水下传感器(DNUS)系统是一种高效节能的海洋环境监测技术。与常见的声波断层扫描方法不同,这种新方法可以利用邻近传感器之间的数据局部重建洋流。考虑到洋流在短时间间隔内高度相关,本文提出了一种基于卡尔曼滤波的跟踪方法,以改进基于dna的洋流估计。采用二维海洋模式生成综合观测数据。仿真结果表明,在引入以往海流估计信息的情况下,该方法优于传统的基于dnus系统的海流制图方法。
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