Publication Type : Conference Paper
Publisher : Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016, Institute of Electrical and Electronics Engineers Inc.
Source : Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016, Institute of Electrical and Electronics Engineers Inc. (2016)
Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992079509&partnerID=40&md5=2910e6c51dbfdf61a6538c4b72d05ac5
ISBN : 9781509012770
Keywords : Bandpass filters, Buoys, Coastal area, Computer circuits, Estimation, Gaussian noise (electronic), Gaussian white noise, Input datas, Kalman filter algorithms, Kalman filters, Mathematical expressions, Reconfigurable hardware, Specific location, Time interval, Tsunamis, Water waves, Wave heights, White noise
Campus : Coimbatore
School : School of Engineering
Center : Electronics Communication and Instrumentation Forum (ECIF)
Department : Electronics and Communication
Year : 2016
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.
Cite this Research Publication : V. Seshadri, Sudheesh, P., Dr. Jeyakumar G., and Dr. Jayakumar M., “Tracking the Variation of Tidal Stature using Kalman Filter”, in Proceedings of IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2016, 2016.