Multiple hypothesis tracking based on the Shiryayev sequential probability ratio test

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• 作者：Jinbin Fu ; Jinping Sun ; Songtao Lu ; Yingjing Zhang
• 关键词：multiple target tracking ; multiple hypothesis tracking ; Shiryayev sequential probability ratio test ; track management ; track score
• 刊名：SCIENCE CHINA Information Sciences
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：59
• 期：12
• 全文大小：372 KB
• 刊物类别：Computer Science
• 刊物主题：Chinese Library of Science
  Information Systems and Communication Service
  
• 出版者：Science China Press, co-published with Springer
• ISSN：1869-1919
• 卷排序：59

文摘

To date, Wald sequential probability ratio test (WSPRT) has been widely applied to track management of multiple hypothesis tracking (MHT). But in a real situation, if the false alarm spatial density is much larger than the new target spatial density, the original track score will be very close to the deletion threshold of the WSPRT. Consequently, all tracks, including target tracks, may easily be deleted, which means that the tracking performance is sensitive to the tracking environment. Meanwhile, if a target exists for a long time, its track will have a high score, which will make the track survive for a long time even after the target has disappeared. In this paper, to consider the relationship between the hypotheses of the test, we adopt the Shiryayev SPRT (SSPRT) for track management in MHT. By introducing a hypothesis transition probability, the original track score can increase faster, which solves the first problem. In addition, by setting an independent SSPRT for track deletion, the track score can decrease faster, which solves the second problem. The simulation results show that the proposed SSPRT-based MHT can achieve better tracking performance than MHT based on the WSPRT under a high false alarm spatial density.