Asynchronous track-to-track association algorithm based on similarity degree of interval-real sequence

被引:0
|
作者
Yi, Xiao [1 ]
Han, Jianyue [1 ]
Zhang, Huaiwei [1 ]
Guan, Xin [1 ]
机构
[1] Department of Electronic and Information Engineering, Naval Aeronautical Engineering Institute, Yantai
来源
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2015年 / 36卷 / 04期
基金
中国国家自然科学基金;
关键词
Asynchronous track; Information fusion; Interval grey number; Target tracking; Track association;
D O I
10.7527/S1000-6893.2014.0275
中图分类号
学科分类号
摘要
Because local sensors in the distributed multi-target tracking system usually start working at different time and provide tracks at different rates with different communication delays, the local tracks from different sensors are usually asynchronous. The current solution is to synchronize the tracks before track association. But the estimation error spreads when synchronizing, which affects the performance of correlation. To solve the problem, an asynchronous track-to-track association method based on similarity degree of interval-real sequence is presented. Firstly, the track sequences are transformed to same-length sequences which contain interval data and real data by interval-real sequence transform (IRST). Then a new difference measurement for the sequences is defined, by which the correlation degree can be calculated and the track association conclusion be made. Simulation results show that the presented method can effectively solve the asynchronous track-to-track association problem, and its performance is seldom affected in the case of different communication delays and disorderly data. ©, 2015, AAAS Press of Chinese Society of Aeronautics and Astronautics. All right reserved.
引用
收藏
页码:1212 / 1220
页数:8
相关论文
共 15 条
  • [1] Tian X., Bar-Shalom Y., Track-to-track fusion configurations and association in a sliding widow, Journal of Advances in Information Fusion, 4, 2, pp. 146-164, (2009)
  • [2] Rafati A., Moshiri B., Rezaei J., A new algorithm for general asynchronous sensor bias estimation in multisensor multi-target systems, Proceedings of 10th International Conference on Information Fusion, pp. 296-301, (2007)
  • [3] Qi Y.Q., Jing Z.L., Hu S.Q., General solution for asynchronous sensors bias estimation, Proceedings of 11th International Conference on Information Fusion, pp. 258-264, (2008)
  • [4] He Y., Wang G.H., Guan X., Et al., Information Fusion Theory with Applications, pp. 10-12, (2010)
  • [5] Pan Q., Liang Y., Yang F., Et al., Modern Target Tracking and Information Fusion, pp. 65-77, (2009)
  • [6] Zhu H.Y., Han C.Z., Han H., Asynchronous track-to-track association method in distributed multi-sensor information fusion system, Control Theory and Applications, 21, 3, pp. 453-456, (2004)
  • [7] Cheng Z., Li H., Zhang A., Algorithmvfor multi-sensor asynchronous track association based on pseudo measurement, Chinese Journal of Sensors and Actuators, 19, 3, pp. 878-881, (2006)
  • [8] Tian X., Bar-Shalom Y., Sliding window test vs. single time test for track-to-track association, Proceedings of 11th International Conference on Information Fusion, pp. 1-8, (2008)
  • [9] Guo Y.H., Yuan C., A mutation ant colony algorithm for the asynchronous track correlation, Acta Electronica Sinica, 40, 11, pp. 2200-2205, (2012)
  • [10] Liu W.F., Wen C.L., A track association algorithm based on the OSPA distance, Acta Aeronautica et Astronautica Sinica, 33, 6, pp. 1083-1092, (2012)