An Algorithm for Retrieving Water Surface Current by Using K-Band Coherent Radar

• Published in: IEEE geoscience and remote sensing letters Vol. 21; pp. 1 - 5
• Main Authors: Guo, Yu, Chen, Zhongbiao, Zhu, Shiping, He, Yijun, Sun, Runxia
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Coherent radar; Continuous wavelet transform; Current velocity; Doppler effect; Doppler radar; K-band; K-band coherent radar; Neural networks; Radar; Radar clutter; Radar echoes; Sea surface; surface currents; Surface treatment; Surface waves; Temporal resolution; Velocity; wavelet analysis
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2024.3405726

Water surface current velocity is an important hydrologic parameter. A novel method for retrieving surface current velocities by using K-band coherent radar is proposed. First, to mitigate the impact of noise on radar echo, a convolutional neural network (CNN) is employed to extract the main wave pattern from orthogonal radar echoes. Second, to retrieve the current velocity with high temporal resolution, a method based on continuous wavelet transform is developed. The proposed method is validated by using a K-band radar and a wave channel in field experiment. For current velocities in the range of 0-1.8 m/s, the average error between the retrieved current velocities and the true velocities is less than 0.07 m/s, and the root mean square errors between them range from 0.03 to 0.16 m/s, indicating that the proposed method is reasonable. Finally, the application condition of the method is discussed.