Trend and Bounds for Error Growth in Controlled Lagrangian Particle Tracking
Trend and Bounds for Error Growth in Controlled Lagrangian Particle Tracking
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DOI：
10.1109/joe.2012.2236491
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发表时间：
2014-01-01
影响因子：
4.1
通讯作者：
Zhang, Fumin
中科院分区：
文献类型：
--
作者：
Szwaykowska, Klementyna;Zhang, Fumin
建立受控拉格朗日粒子跟踪（CLPT）方法，分析海洋机器人在海洋中的物理位置与受控粒子在海洋模型中的模拟位置之间的偏差。我们称之为CLPT误差的偏移显示了以前在无法主动控制的漂移器和浮动器中看不到的显著特性。CLPT误差随着时间的推移呈指数增长，直到它达到一个转折点，这只取决于海洋模型的分辨率。在这个转折点之后，误差增长显著减缓到时间的多项式函数。在理想情况下，可以推导出CLPT误差指数增长的理论上限。理论上证明了这些特性，通过模拟验证，并与海洋实验数据的合理性。CLPT方法可用于提高海洋环流模型的精度和海洋机器人导航算法的性能。
This paper establishes the method of controlled Lagrangian particle tracking (CLPT) to analyze the offsets between physical positions of marine robots in the ocean and simulated positions of controlled particles in an ocean model. The offset, which we term the CLPT error, demonstrates distinguished characteristics not previously seen in drifters and floats that cannot be actively controlled. The CLPT error growth over time is exponential until it reaches a turning point that only depends on the resolution of the ocean model. After this turning point, the error growth slows down significantly to polynomial functions of time. In the ideal case, a theoretical upper threshold on exponential growth of CLPT error can be derived. These characteristics are proved theoretically, verified via simulation, and justified with ocean experimental data. The method of CLPT may be applied to improve the accuracy of ocean circulation models and the performance of navigation algorithms for marine robots.