Chinese Journal of Lasers, Volume. 45, Issue 10, 1010001(2018)
Adaptive Depth Extraction Algorithm for Ocean Lidar
The laser pulse emitting from the ocean lidar would be stretched while it travels through the deep sea water, and the waveform received by the ocean lidar is quite different from the emitting signal. Therefore, the normal matched filtering algorithm using emitting signal as the matched filtering has a bad performance in processing ocean Lidar data. To improve the performance of matched filtering algorithm, Mento Carlo method is used to simulate the signal waveforms at different depths. The simulation waveforms are used as the matched filtering at the corresponding depth. The adaptive depth extraction algorithm is tested on the data set which is measured in the South China Sea. The test shows that the adaptive depth extraction algorithm is more accurate and robust on ocean lidar data set. A set of single beam sonar data is used to evaluate the accuracy of depth using the adaptive depth extraction algorithm.
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Liu Menggeng, He Yan, Chen Weibiao, Wang Yongxing, Zhu Xia, Shi Xiangao, Huang Tiancheng, Zhang Yufei. Adaptive Depth Extraction Algorithm for Ocean Lidar[J]. Chinese Journal of Lasers, 2018, 45(10): 1010001
Category: remote sensing and sensor
Received: Mar. 16, 2018
Accepted: --
Published Online: Oct. 12, 2018
The Author Email: Yan He (heyan@mail.chcnc.ac.cn)