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首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Comprehensive Track Segment Association for Improved Track Continuity
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Comprehensive Track Segment Association for Improved Track Continuity

机译：全面的赛道段关联，提高了赛道的连续性

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摘要

Track breakages are common in target tracking due to highly maneuvering targets, association with false alarms or incorrect target-originated measurements, low detection probability, close target formations, large measurement errors, and long sampling intervals, among other causes. Existing track segment association (TSA) algorithms solve this breakage problem by predicting old track segments and retrodicting young track segments to a common time followed by two-dimensional (2-D) assignment. This approach presents two disadvantages. First, these algorithms predict or retrodict from the actual point of termination or beginning of their respective tracks, that is, they neither check if the cause of a track termination was incorrect association nor redress such an erroneous association. Second, these algorithms do not utilize the measurement information during the breakage period. Often, track terminations are due to incorrect measurement association. To solve the first problem, this paper proposes a 2-D assignment-based TSA algorithm that releases incorrectly associated measurements by going backward and forward in time along old and young track segments, respectively, and then performing prediction and retrodiction. Furthermore, to address both shortcomings in existing TSA algorithms simultaneously, we propose a novel multiframe assignment-based TSA algorithm that estimates the track during the breakage period, utilizing both unassociated and released measurements simultaneously. Moreover, the proposed algorithms can handle target maneuvers subject to a single turn during the breakage period. In the proposed solution, model parameters, such as starting time of the turn, ending time of the turn, and turn rate are obtained by maximizing the likelihood that a given measurement-tuple originated from the track couple under consideration. Simulation results demonstrate that the proposed TSA algorithm is superior to existing ones in terms of association accuracy and computational cost.
机译：在目标跟踪中，由于目标机动性高，与虚假警报或不正确的目标起源的测量值相关联，检测概率低，目标形成接近，测量误差大以及采样间隔长等原因，磁道断裂在目标跟踪中很常见。现有的轨道段关联（TSA）算法通过预测旧的轨道段并将新的轨道段追溯到公共时间，然后进行二维（2-D）分配来解决此断裂问题。这种方法存在两个缺点。首先，这些算法从实际终止点或它们各自轨迹的开始点进行预测或追溯，即它们既不检查轨迹终止的原因是否是错误的关联，也不纠正这种错误的关联。其次，这些算法在中断期间不使用测量信息。通常，轨迹终止是由于错误的测量关联引起的。为了解决第一个问题，本文提出了一种基于二维分配的TSA算法，该算法通过沿旧轨道段和年轻轨道段分别在时间上向前和向后前进，然后执行预测和追溯来释放不正确的关联测量值。此外，为了同时解决现有TSA算法中的两个缺点，我们提出了一种新颖的基于多帧分配的TSA算法，该算法可同时利用未关联和已释放的测量值来估计断裂期间的轨道。而且，所提出的算法可以在破损周期内单转处理目标机动。在提出的解决方案中，通过最大化给定的测量元组源自所考虑的磁道对的可能性来获得模型参数，例如转弯的开始时间，转弯的结束时间和转弯速率。仿真结果表明，所提TSA算法在关联精度和计算成本上均优于现有算法。

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