Abstract
To obtain accurate underwater target tracking results, an improved kernelized correlation filter (IKCF) algorithm is proposed to track the target in forward-looking sonar image sequences. Specifically, a base sample with a dynamically continuous scale is first applied to solve the poor performance of fixed-scale filters. Then, in order to prevent the filter from drifting when the target disappears and appears again, an adaptive filter update strategy with the peak to sidelobe ratio (PSR) of the response diagram is developed to solve the following target tracking errors. Finally, the experimental results show that the proposed IKCF can obtain accurate tracking results for the underwater targets. Compared to other algorithms, the proposed IKCF has obvious superiority and effectiveness.
Highlights
With the rapid development of the world economy, the strategic position of the ocean has become more and more important [1]
improved kernelized correlation filter (IKCF) for underwater target tracking in forward-looking sonar image sequences; the experimental data are the real forward-looking sonar data obtained in Qiandao Lake
To demonstrate the effectiveness of the proposed IKCF for tracking the normal target, the 1st frame to the 60th frame are selected in forward-looking sonar image sequences
Summary
With the rapid development of the world economy, the strategic position of the ocean has become more and more important [1]. Quidu et al [8] introduced the KF for multitarget tracking in forward-looking sonar image sequences; this algorithm was designed for still target lying on a flat seafloor. On this basis, a framework using navigation data for performing robust multitarget tracking based on the KF is proposed to track an obstacle in a series of sonar images [9], but this work cannot be used for the tracking of moving obstacles. Reference [19] adopted a deformable part-based correlation filter tracking approach to cope with challenging cases, like partial occlusion, deformation, or scale changes In these regards, to obtain more accurate tracking results, this paper presents an improved kernelized correlation filter (IKCF) to track the underwater target in forward-looking sonar image sequences. The proposed IKCF has important theoretical and practical value
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