Iteratively weighted center of gravity algorithm used for depth extraction of streak image

Streak array detecting lidar has advantages of high ranging accuracy, long detecting distance, wide ranging gate and high data acquiring rate, which is widely used in topographic mapping, coastal zone monitoring, urban 3D remodeling, forest ecological research etc. The traditional method on signal discrimination has some limitations in the depth extraction of echo signal, which affects the capability of depth distinguish and target recognition of streak array detecting lidar. For this problem, an iteratively weighted centroid algorithm was introduced while dealing the streak images and the unique advantages on centroid location of the algorithm were discussed. The key parameters of the algorithm were determined according to signal distribution character of streak array detecting lidar. By using this algorithm, the range image with clear boundary feature of a target was obtained at the distance of 1.4 km. The boundary blurring effect was effectively suppressed in the depth extraction process and the resolution ability of the system was improved. Compared with traditional centroid algorithm, the ranging accuracy was improved by 17%.