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A Real-Time Filtering Approach for Plot-Sequences Outputted by Multi - Frame Track - Before- Detection

机译:多帧跟踪-检测前输出的绘图序列的实时滤波方法

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This paper addresses the real-time filtering problem respect to the multi-frame track-before-detection (MF - TBD). Instead of making detections on each single frame, MF - TBD jointly processes multiple raw data frames at each time, which can remain and utilize more target information. Thus, different from the conventional detection procedure which provides single point plot to a tracker, output of MF - TBD is plot-sequence. However, for batch processing MF - TBD, there are repetitive parts (named plot-sets) under a number of consecutive batches in time series while the correlation among each plot in the plot-set is complex and unpractical to computation. In this paper, by avoiding the computation of correlation, a novel filtering approach is developed for the plot-sequences outputted by batch processing MF - TBD. Last, simulation results show that the proposed algorithm can correctly estimate target trajectories and significantly enhance the tracking accuracy compared with the MF - TBD without our filtering algorithm.
机译:本文针对多帧检测前跟踪(MF-TBD)问题解决了实时过滤问题。 MF-TBD不会在每个帧上都进行检测,而是每次都联合处理多个原始数据帧,这些原始数据帧可以保留并利用更多的目标信息。因此,与向跟踪器提供单点绘图的常规检测程序不同,MF-TBD的输出为绘图序列。但是,对于批处理MF-TBD,在时间序列的多个连续批次下有重复的部分(称为图集),而在图集中每个图之间的相关性很复杂,计算上不切实际。在本文中,通过避免相关性的计算,针对批处理MF-TBD输出的绘图序列,开发了一种新颖的滤波方法。最后,仿真结果表明,与不带滤波算法的MF-TBD算法相比,该算法可以正确估计目标轨迹,并显着提高跟踪精度。

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