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Using fractal dimension or one of other fractal characteristics to detect targets in sea clutter, it is often difficult to distinguish at low signal-to-clutter ratios. To solve this problem, a new method for target detection in sea clutter based on combined fractal characteristics is proposed. The detection process is divided into two stages: coarse detection and fine detection. When the fractal spectrum...
In this paper, we consider the fluctuating targets detection problem in a distributed multi-sensor network. A multi-sensor multi-frame track-before-detect (MS-MF-TBD) procedure is proposed to sufficiently make use of the target energy diversity in space and time dimensions (space-time diversity). Two MS-MF-TBD methods, the multi-sensor maximum likelihood-probabilistic data association (MS-ML-PDA)...
Hough voting based methods for object detection work by means of allowing local image patches to vote for the center of the object according to the trained visual words. They are effective for object with small local varieties, but incapable of solving multi-view detection problem. The traditional way is training visual words for each subcategory that has similar view. However, limited training data...
We consider the problem of point target detection on images and focal plane arrays (FPA). Imaging sensors are becoming ubiquitous tools in several applications, such as biomedical systems, autonomous surveillance systems, target tracking systems, and robotics. In these applications, matched filter and template matching are commonly used detection strategies, however, these approaches are unable to...
Multi-sensor fusion has been extensively studied i information fusion field, and the distributed target detection i one of the most important applications in the multiple sensor detection theories. In this paper, a data fusion algorithm for target detection is proposed based on tree topology combine with the orderly full binary tree and we discuss the optima threshold fusion rule problem. Different...
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