中国激光, 2018, 45 (10): 1010001, 网络出版: 2018-10-12
海洋激光雷达的自适应深度提取算法 下载: 841次
Adaptive Depth Extraction Algorithm for Ocean Lidar
遥感 机载激光测深 匹配滤波算法 海底数值高程 remote sensing airborne laser bathymetry matched filtering algorithm digital elevation model of depths
摘要
海洋激光雷达发射的激光脉冲在海水中传输, 脉冲波形随深度会发生展宽, 相应的雷达接收系统接收到的信号与激光发射脉冲差异会增大, 该现象会导致以发射脉冲作为匹配滤波器的固定匹配滤波方法在处理深水激光雷达回波信号时产生误判。为了改进匹配滤波算法对于海洋激光雷达回波数据的性能, 使用蒙特卡罗法研究在测区条件下不同深度的激光脉冲在雷达探测器上的波形, 并以这组波形作为深度自适应的匹配滤波器来代替匹配滤波算法中的固定匹配滤波器, 并用南海的实测数据检验算法的性能。实验表明, 自适应深度提取算法相比于匹配滤波算法稳定性和准确性更好。为了验证算法的正确性, 以单波束声呐测深在同一测区的测深数据为基础, 对雷达测深数据进行精度评定。
Abstract
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.
刘梦庚, 贺岩, 陈卫标, 王永星, 朱霞, 石先高, 黄田程, 张宇飞. 海洋激光雷达的自适应深度提取算法[J]. 中国激光, 2018, 45(10): 1010001. 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.