Three-dimensional imaging of ships in the foggy environment using a single-photon detector array.

When using single-photon detector array lidar to detect ships in a foggy environment, the multiple scattering between laser and sea fog, sea surface and ships leads to a large number of fake images in the reconstructed depth images, which seriously limits the ability to detect and recognize ships. Here, we propose a three-dimensional imaging algorithm suitable for ships in fog with a single-photon detector array lidar. This algorithm can eliminate fake images caused by multiple reflections of the sea surface in a foggy environment. Firstly, the algorithm uses a dual-Gamma estimation algorithm to eliminate the influence of non-signal photons, and uses a pulse-like selection algorithm to accurately extract the target echo waveform. Secondly, based on the characteristics of the target echo, the principal component analysis (PCA) and K-means algorithm are used to cluster the features of the separated echo signals. Finally, the result of feature classification is used to achieve efficient fake images removal. We show that the proposed algorithm can more accurately reconstruct the depth image of a ship with a distance of 1.72 km in fog environment. Compared with the traditional algorithms, the proposed algorithm can suppress the sea surface reflection while retaining the most target contour. It has been successfully demonstrated for small ships at different distances. This research is expected to improve the detection and recognition ability of single-photon detector array lidar for small targets in complex scenes. [ABSTRACT FROM AUTHOR]