@inproceedings{5b456b68fe81440caace5c952b3153dd,
title = "A new multi-sensor track association approach based on intuitionistic fuzzy clustering",
abstract = "To extend some multi-target trackers to a multi-sensor scenario for improving their accuracy and dependable, an efficient track association and fusion algorithm is necessary. This paper proposes a new track association approach which imports the intuitionistic fuzzy set into track association. The proposed method firstly transforms the extracted target states into intuitionistic fuzzy sets, then makes use of the clustering intuitionistic fuzzy sets to obtain an equivalent association matrix, and finally associates and fuses the states from different sensors with the equivalent matrix. The numerical simulation results show that this method can significantly control the time cost and performs better compared with the association algorithm with fuzzy clustering.",
keywords = "Intuitionistic fuzzy sets, Multi-sensor, Multi-target tracking, Track association",
author = "Zhao Lingling and Dong Xianglei and Ma Peijun and Su Xiaohong and Shi Chunmei",
year = "2013",
doi = "10.1007/978-3-319-03783-7\_23",
language = "英语",
isbn = "9783319037820",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "256--266",
booktitle = "Advances in Information Technology - 6th International Conference, IAIT 2013, Proceedings",
address = "德国",
note = "6th International Conference on Advances in Information Technology 2013, IAIT 2013 ; Conference date: 12-12-2013 Through 13-12-2013",
}