Tracking the variation of tidal stature using Kalman filter

V. Seshadri, P. Sudheesh, M. Jayakumar
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引用次数: 8

Abstract

The intent of this paper is to track the height of a tidal wave, using the Kalman filter. By using the Kalman filter algorithm, mathematical expressions are derived to determine the height of a tidal wave. By placing buoy sensors at specific locations in the sea, the real tidal wave height is measured. The buoy sensor is placed at a particular distance from the shore. The sensors continuously record data at that particular position at different time intervals and then transmit the data to the receiver on the shoreline. By continuously evaluating this data, the height of the next wave is being estimated. Since a buoy cannot be placed at every point of the wave, this method provides an easy estimation of replicating the process. These sensors are used to simulate the proposed method of tracking the height of a tidal wave and hence giving a warning in advance in case of a wave height which is more than normal. This warning helps people living in coastal areas to vacate the place in advance, therefore avoiding fatality. This tracking of the tidal wave height is useful particularly in the case of a tsunami. By adding Gaussian white noise to the input data from the buoy sensors, a prediction of the next wave height is possible.
利用卡尔曼滤波跟踪潮汐高度的变化
本文的目的是利用卡尔曼滤波来跟踪潮汐波的高度。利用卡尔曼滤波算法,导出了确定潮汐波高度的数学表达式。通过在海上的特定位置放置浮标传感器,可以测量真实的潮汐波高。浮标传感器被放置在离海岸一定距离的地方。传感器以不同的时间间隔连续记录特定位置的数据,然后将数据传输到海岸线上的接收器。通过不断地评估这些数据,就可以估计出下一波的高度。由于浮标不能放置在波浪的每个点,这种方法提供了一个简单的估计复制的过程。这些传感器用来模拟所提出的跟踪潮汐高度的方法,从而在波浪高度超过正常水平时提前发出警告。这一警告有助于居住在沿海地区的人们提前撤离,从而避免死亡。这种对潮汐波高度的跟踪是有用的,特别是在海啸的情况下。通过在浮标传感器的输入数据中加入高斯白噪声,可以预测下一波的高度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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