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A sequential detection approach to target tracking

机译:目标跟踪的顺序检测方法

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Sequential hypothesis testing is investigated for multiframe detection and tracking of low-observable maneuvering point-source targets in a digital image sequence. The proposed multiple multistage hypothesis test tracking (MMHTT) algorithm extends tracks formed from sequentially detected target trajectory segments using a multiple hypothesis tracking strategy. The MMHTT algorithm does not require a probabilistic larger maneuver model. Computational efficiency is achieved by using a truncated sequential probability ratio test (SPRT) to prune a dense tree of candidate target trajectories and score the detected trajectory segments. An analytical performance evaluation is presented and confirmed by experimental results from an optical satellite tracking application.
机译:研究了顺序假设检验,用于多帧检测和跟踪数字图像序列中低可观察的机动点源目标。提出的多阶段假设测试跟踪(MMHTT)算法使用多重假设跟踪策略扩展了从顺序检测到的目标轨迹段形成的跟踪。 MMHTT算法不需要概率较大的机动模型。通过使用截断的顺序概率比率测试(SPRT)修剪候选目标轨迹的密集树并对检测到的轨迹段进行评分,可以实现计算效率。提出了一种分析性能评估,并通过光学卫星跟踪应用的实验结果进行了确认。

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