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Water 2016, 8(6), 262; doi:10.3390/w8060262

Micro Radar Surface Velocimetry for Hydrologic Signal Processing Using a Bandpass Filtering Approach

1
Department of Civil Engineering, Feng Chia University, Taichung 40724, Taiwan
2
Ph.D. Program in Civil and Hydraulic Engineering & Research Center for Science and Technology across the Taiwan Strait, Feng Chia University, Taichung 40724, Taiwan
3
Department of Water Resources Engineering and Conservation, Feng Chia University, Taichung 40724, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Y. Jun Xu
Received: 21 March 2016 / Revised: 13 June 2016 / Accepted: 15 June 2016 / Published: 21 June 2016
View Full-Text   |   Download PDF [2645 KB, uploaded 21 June 2016]   |  

Abstract

The collection of hydrological data is particularly important for the utilization and management of water resources, water conservation, and flood control. Most of the hydrological observation operations should be conducted manually and are time-consuming, strenuous, dangerous, and have low precision. In this study, the shortcomings of the manual observations are overcome and the uncertainties related to the radar-based flow velocity estimations by a sensor in the radar surface current meter are explored. This includes an automatic observation feature and analyses are conducted using the radar signals that are received by the instruments for the real-time observation of the signals. In this study, experiments were conducted at the Water Resources Planning Institute (WRPI) of the Water Resources Agency, Ministry of Economic Affairs, Taiwan and the surface velocity was estimated using the conventional fast Fourier transform (FFT), wavelet transform (WT), and a bandpass filter. The experimental results after signal processing using the bandpass filter were precise, when the tilt angle ranged between 20 and 40 degrees. The 10.525 GHz radar surface current meter adopted in this study is suitable for a tilt angle of 20–40 degrees; the measurement error will be relatively large if the tilt angle is less than 20 degrees or more than 40 degrees. View Full-Text
Keywords: bandpass filter; hydrologic signal processing; micro radar surface velocimetry; fast Fourier transform; wavelet transform bandpass filter; hydrologic signal processing; micro radar surface velocimetry; fast Fourier transform; wavelet transform
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Lin, J.-W.; Huang, C.-W.; Hsu, Y.-S. Micro Radar Surface Velocimetry for Hydrologic Signal Processing Using a Bandpass Filtering Approach. Water 2016, 8, 262.

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