ACOUSTIC OBSTACLE DETECTION FOR SAFE AUV SURFACING

Abstract

International audienceWe propose an automatic sea surface object detection from forward lookingsonar images. The considered sea surface obstacles are man-made objects: buoys, boats,ships (motorboats or sailboats). Their acoustic signature varies according to their typeand state (fixed or moving).The proposed detection scheme is hierarchical in order to manage the various targetsignatures. The first step consists in detecting stationary self noise from ships. In case ofdetection, the strong-intensity strip corresponding to the ship direction is removed toavoid ship noise disturbance during other target detection processes. The next stepconsists in detecting the other types of obstacles. It is based on an adaptive CFAR(Constant False Alarm Rate) thresholding. The final step consists in analyzing the areaaround every detected position in order to state that this latter is a reliable obstacle andnot a wake signature. Promising results are obtained using real data collected at sea withvarious objects and scenarios