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    杜思伟, 林家骏. 一种针对于状态估计算法的敏感指标构建方法[J]. 华东理工大学学报(自然科学版), 2012, (5): 629-634.
    引用本文: 杜思伟, 林家骏. 一种针对于状态估计算法的敏感指标构建方法[J]. 华东理工大学学报(自然科学版), 2012, (5): 629-634.
    DU Si-wei, LIN Jia-jun. An Approach of Constructing Sensitive Metric for State Estimation Algorithm[J]. Journal of East China University of Science and Technology, 2012, (5): 629-634.
    Citation: DU Si-wei, LIN Jia-jun. An Approach of Constructing Sensitive Metric for State Estimation Algorithm[J]. Journal of East China University of Science and Technology, 2012, (5): 629-634.

    一种针对于状态估计算法的敏感指标构建方法

    An Approach of Constructing Sensitive Metric for State Estimation Algorithm

    • 摘要: 针对信息融合领域内状态估计算法的性能评估问题,分析了当前常用评估指标的不足。提出了一种基于最优子模式分配的敏感指标构建方法,该指标利用两个可控参数对点迹位置误差与关联误差的敏感度进行合理分配。通过两组不同条件的实验,证明了在单目标环境下,OSPA距离具有与位置均方根误差相同的有效性与评估准确度;在多目标环境下,OSPA距离具有更高的使用灵活度与敏感度。

       

      Abstract: For the performance evaluation of state estimation algorithm in the field of information fusion, this paper analyzes the shortcoming of conventional evaluation indexes and proposes a constructing method of sensitive index based on optimal subpattern assignment. The sensitivity of this metric can be reasonably distributed to location error and association error by using two controllable parameters. By simulating under two different conditions, it is shown that OSPA distance not only has the same validity and accuracy of performance evaluation as the mean square root error of position in a singletarget environment, but also has higher flexibility and sensitivity in a multitarget environment.

       

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