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Article Dans Une Revue IEEE Transactions on Geoscience and Remote Sensing Année : 2015

Automatic Sea-Surface Obstacle Detection and Tracking in Forward-Looking Sonar Image Sequences

Isabelle Quidu
Michel Legris

Résumé

Automatic sea-surface object detection and tracking for safe autonomous underwater vehicle and submarine surfacing is a critical issue in relation to the accidents reported in the last decades. Here, we propose an efficient tool to detect and track sea-surface obstacles by processing forward-looking sonar images. The proposed method can detect either still or moving objects with and without wake. For each image sequence, a sequential procedure is proposed to detect various obstacle signatures. Then, target positions and velocities are estimated in Cartesian coordinates using the debiased converted measurement Kalman filter and the joint probabilistic data association filter. Detection and tracking stages exchange information in order to reduce the number of false alarms. Promising results are obtained using real data collected at sea with various objects and scenarios.
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Dates et versions

hal-01203532 , version 1 (23-09-2015)

Identifiants

Citer

Imen Karoui, Isabelle Quidu, Michel Legris. Automatic Sea-Surface Obstacle Detection and Tracking in Forward-Looking Sonar Image Sequences. IEEE Transactions on Geoscience and Remote Sensing, 2015, Geoscience and Remote Sensing, IEEE Transactions on, 53 (8), pp.4461-4469. ⟨10.1109/TGRS.2015.2405672⟩. ⟨hal-01203532⟩
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