New Accuracy Evaluation Index for Track Fusion Algorithms

doi:10.1007/s12204-019-2130-2

Abstract

Abstract: When evaluating the track fusion algorithm, common accuracy indexes may fail to evaluate the fusion accuracy correctly when the state estimation and the real target cannot be one-to-one, and fail to effectively distin- guish the performance of the algorithm when the state estimation is similar. Therefore, it is necessary to construct a high-resolution evaluation index, which can evaluate the track fusion algorithm more accurately, reasonably and comprehensively. Firstly, the advantages and disadvantages of the optimal subpattern assignment(OSPA)distance as the accuracy index to evaluate the track fusion algorithm are analyzed. Then, its deficiencies are improved by using the Hellinger distance instead of the original Euclidean distance, and the distance is index transformed. Finally, a new evaluation index for track fusion algorithms is proposed, which is the OSPA distance based on Hellinger distance and index transformation. The simulation results show that the new index can not only cor- rectly evaluate the fusion precision, but also consider the state uncertainty, making that can evaluate the track fusion algorithm more sensitively, and e?ectively solves the sensitivity of the index to the cut-off parameter c through index transformation.

Key words: track fusion algorithm| evaluation index| optimal subpattern assignment distance| Hellinger distance| index transformation

摘要： When evaluating the track fusion algorithm, common accuracy indexes may fail to evaluate the fusion accuracy correctly when the state estimation and the real target cannot be one-to-one, and fail to effectively distin- guish the performance of the algorithm when the state estimation is similar. Therefore, it is necessary to construct a high-resolution evaluation index, which can evaluate the track fusion algorithm more accurately, reasonably and comprehensively. Firstly, the advantages and disadvantages of the optimal subpattern assignment(OSPA)distance as the accuracy index to evaluate the track fusion algorithm are analyzed. Then, its deficiencies are improved by using the Hellinger distance instead of the original Euclidean distance, and the distance is index transformed. Finally, a new evaluation index for track fusion algorithms is proposed, which is the OSPA distance based on Hellinger distance and index transformation. The simulation results show that the new index can not only cor- rectly evaluate the fusion precision, but also consider the state uncertainty, making that can evaluate the track fusion algorithm more sensitively, and e?ectively solves the sensitivity of the index to the cut-off parameter c through index transformation.

关键词: track fusion algorithm| evaluation index| optimal subpattern assignment distance| Hellinger distance| index transformation

CLC Number:

TH 701

LI Yuewu (李月武), HU Jianwang (胡建旺), JI Bing (吉兵), CHEN Zizhao (陈子兆). New Accuracy Evaluation Index for Track Fusion Algorithms[J]. Journal of Shanghai Jiao Tong University (Science), 2020, 25(1): 97-105.

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