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Joint IMM/MHT Tracking and Identification with Confusers and Track Stitching

机译:与混淆者进行IMM / MHT联合跟踪和识别以及跟踪拼接

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It is widely accepted that Classification Aided Tracking (CAT) has the potential to maintain continuous tracks on important targets. Moreover, when augmented with target behavior, a joint tracking and ID system can enhance the data association process for ground tracking systems. It is also recognized that it is likely that some targets in any scenario may not be included in a database, and the presence of such confusers would diminish both tracking and ID performance. Moreover, even with ID information, tracks may switch targets. Thus, a joint tracking and identification architecture has been developed which addresses the issues of both confusers and track ID switching. These methods are being tested using simulated dynamic ground targets and radar High Range Resolution (HRR) data provided by the Moving and Stationary Target Acquisition and Recognition (MSTAR) project. The paper begins by giving an overview of the IMM/MHT tracker that has been designed to handle the unique characteristics (such as on-off road behavior) of the ground target tracking problem. Then, a joint tracking identification methodology is described. Implementing this approach, target behavior (such as being part of a group, speed, and on/off road motion) can be used both in the data association and for target type information. A Dempster-Shafer method is used for combining all classification-related data. In addition, confusers are taken into account by incorporating the information from targets that are in the database. The track score, required in all MHT data association decisions, is augmented with a feature-related term derived from the conflict term computed from an application of Dempster's Rule. The histories of the most likely ID for each track are checked to identify possible switches, and if tracks are believed to have switched IDs, then the state and the covariances of these tracks are exchanged so that future observations may be consistent with the original targets. Finally, the paper illustrates the proposed methods using results from a detailed simulation of target convoys, with and without confuser targets, that perform on and off road maneuvers. Results using MSTAR HRR data are presented for Classification-Aided (CAT) approaches to feature-aided tracking.
机译:众所周知,分类辅助跟踪(CAT)具有在重要目标上保持连续跟踪的潜力。此外,当增加目标行为时,联合跟踪和ID系统可以增强地面跟踪系统的数据关联过程。还应认识到,任何情况下的某些目标都有可能未包含在数据库中,并且此类混淆器的存在会降低跟踪和ID性能。而且,即使具有ID信息,轨道也可以切换目标。因此,已经开发了一种联合跟踪和标识体系结构,该体系结构解决了混淆器和跟踪ID切换两者的问题。这些方法正在使用模拟的动态地面目标和由移动和固定目标获取与识别(MSTAR)项目提供的雷达高分辨力(HRR)数据进行测试。本文首先概述了IMM / MHT跟踪器,该跟踪器旨在处理地面目标跟踪问题的独特特征(例如,开-关道路行为)。然后,描述了联合跟踪识别方法。实施此方法,可以在数据关联中和目标类型信息中使用目标行为(例如,作为一组的一部分,速度和上/下路的运动)。 Dempster-Shafer方法用于组合所有与分类相关的数据。另外,通过合并来自数据库中目标的信息来考虑混淆器。在所有MHT数据关联决策中都需要使用跟踪得分,并增加一个与特征相关的术语,该术语是根据应用Dempster规则计算出的冲突项得出的。检查每个磁道最可能出现的ID的历史记录,以识别可能的切换,如果认为磁道具有切换ID,则将交换这些磁道的状态和协方差,以便将来的观察结果与原始目标保持一致。最后,本文使用对目标车队进行了详细模拟的结果,说明了拟议的方法,该目标车队在有或没有混淆目标的情况下均可执行越野操作。提出了使用MSTAR HRR数据的结果,以用于分类辅助(CAT)方法进行特征辅助跟踪。

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