A Summary of Research on Model Identification and Target Tracking of Non-cooperative Target
Proceeding: Second International Conference on Artificial Intelligence and Pattern Recognition (AIPR2015)Publication Date: 2015-04-16
Authors : Chun Xu; Linfang Yang; Songtao Fan; Jinzhe Jiang;
Page : 1-7
Keywords : non-cooperative target; model identification; target trackin; sparse reconstruction algorithms; compressed sensing;
Abstract
This paper is a survey which mainly studies the model identification and target tracking of the non-cooperative target with no visual feature in space. In order to achieve a visual model for non-cooperative target recognition and attitude tracking, we introduce a compressed sensing and particle filter method, especially no prior knowledge of the visual target. Topics include: (1) research on image reconstruction of non-cooperative target based on com-pressed sensing; (2) research on visual model Identification to non-cooperative targets; (3) research on attitude estimate and target tracking to non-cooperative target gesture based on multi-regional joint particle filter. The aims of this project are: to give sparse reconstruction algorithms for the high dimension image, to give visual model identification method for the non-cooperative target with no visual feature, to solve the problems of attitude estimation and tracking of on-cooperative target based on identification model. Finally, a systematic solution will be given for the docking or capture mission to spacecraft especially the non-cooperative target in space.
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Last modified: 2015-04-18 14:15:07