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Design of a Performance Evaluation Methodology for Data Fusion-based Multiple Target Tracking Systems

机译:基于数据融合的多目标跟踪系统性能评估方法的设计

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摘要

The emphasis of this paper is to design a Performance Evaluation Methodology for Data Fusion-based Multiple Target Tracking Systems. Within this methodology the Performance Evaluation process is treated as a whole new fusion process. This has two major advantages ― (1) Facilitates reusability of existing models and algorithms, and (2) Using standard frameworks and norms makes it easier for the tracking community to easily adopt it ― thus giving this aspect of tracking a highly needed jumpstart. A case study implementation of this design methodology is presented. Three different Track-Truth Association strategies were implemented to study the effect of Track-Truth Association strategies on the performance metrics. The case study results conclusively show that the selection of the Track-Truth Association strategy should be done with reference to the scenario characteristics, the "mission" goals and the performance metrics to be evaluated.
机译:本文的重点是为基于数据融合的多目标跟踪系统设计一种性能评估方法。在这种方法中,性能评估过程被视为一个全新的融合过程。这具有两个主要优点-(1)促进现有模型和算法的可重用性,以及(2)使用标准框架和规范使跟踪社区更容易采用它-从而为跟踪急需的Jumpstart提供了这一方面。提出了这种设计方法的案例研究。实施了三种不同的“真相关联”策略来研究“真相关联”策略对性能指标的影响。案例研究结果最终表明,应根据场景特征,“任务”目标和要评估的性能指标来选择“真相与关联”策略。

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