改进的联合概率数据关联算法

Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997) Pub Date : 2002-07-08 DOI:10.1109/ICIF.2002.1021009

Wang Ming-Hui, Peng Ying-ning, You Zhi-sheng

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引用次数: 7

摘要

联合概率数据关联(JPDA)滤波器在密集目标和重杂波环境下具有很好的跟踪性能。然而，JPDA滤波器也有一个巨大的计算机负载，并倾向于结合邻近的轨道。本文提出了一种改进的JPDA算法。该方法的主要特点是通过改进跟踪门的性能来提高JPDA算法的性能。通过数学分析验证了该方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Improved joint probabilistic data association algorithm

The joint probabilistic data association (JPDA) filter has a very good tracking performance in dense targets and heavy clutter environments. However, the JPDA filter also has a huge computer load and tends to combine neighboring tracks. In this paper, an improved JPDA algorithm is presented. The main feature of our method is improving the performance of the JPDA algorithm by improving the performance of the tracking gate. The effectiveness of this method is assessed by mathematical analysis.

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Proceedings of the Fifth International Conference on Information Fusion. FUSION 2002. (IEEE Cat.No.02EX5997)

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