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.