Underwater Target Detection for Unmanned Surface Vessel Based on Three-Dimensional Imaging Sonar
Aiming at problems about frequent interference in sonar images and the possibility of a sin-gle target splitting into multiple bright spots during the underwater target detection process of un-manned surface vessel(USV),research on underwater target detection technology for USV based on three-dimensional(3D)imaging sonar is carried out.Firstly,considering the need of detection,track-ing and recognition to underwater targets of USV,a 3D point cloud image model is established.Then,a seabed detection algorithm based on random sample consensus(RANSAC)plane fitting is proposed to complete the extraction and separation of seabed planes in the 3D point cloud image.By using tech-nologies of 3D point cloud detection based on Euclidean clustering and multi-feature data association,the probability of target detection is enhanced.Finally,experiment in a lake is carried out.Experimen-tal results verify the effectiveness of the algorithm for underwater target detection and recognition.
3D point cloud imagerandom sample consensus(RANSAC)plane fittingseabed de-tectionEuclidean clusteringmulti-feature data association
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