Asynchronous track-to-track association algorithm based on k means distance of nearest neighbors

被引：0
|
作者：
Yi X. [1 ]
Zeng R. [1 ,2 ]
机构：
[1] Naval Aviation University, Yantai
[2] Unit 92325 of PLA, Datong
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2022年 / 44卷 / 11期
关键词：
asynchronous track; grey relational degree; k means distance of nearest neighbors; multidimensional allocation; track-to-track association;
D O I：
10.12305/j.issn.1001-506X.2022.11.27
中图分类号：
学科分类号：
摘要：
Aiming at the complex problem of local node track-to-track association under asynchronous and unequal rates, an asynchronous track-to-track direct association algorithm based on the k means distance of the nearest neighbors is proposed. First, the k means distance calculation rule of the nearest neighbor between different track sequences is given. Then the gray relational degree among different track sequences are calculated, the classical allocation method is used to determine the track-to-track association. The algorithm does not need time domain registration, and it avoids the accumulation of estimation error propagation. The simulation data show that the algorithm has high correct correlation rate and low time consumption. Asynchronous factors such as inconsistency of sampling period and startup time of local nodes have no obvious influence on the algorithm, and the algorithm is not affected by the change of noise distribution form and targets number. © 2022 Chinese Institute of Electronics. All rights reserved.
引用
收藏
页码：3515 / 3521
页数：6
相关论文
共 17 条
  • [1] LIU Q Y, ZHANG Q., Heterogeneous multi-sensor data fusion in radar signal processing, Proc. of the 4th International Conference on Electromechanical Control Technology and Transportation, pp. 134-137, (2019)
  • [2] YI X, DU J P, CAO X Y, Asynchronous track association of radar and electronic support measurements at different sites, Systems Engineering and Electronics, 43, 4, pp. 954-960, (2021)
  • [3] ZHU H, WANG M L, YUEN K V, Et al., Track-to-track association by coherent point drift, IEEE Signal Processing Letters, 24, 5, pp. 643-647, (2017)
  • [4] ZHENG J C, WANG Y, LIN C C, Et al., A fusion algorithm of target dynamic information for asynchronous multi-sensors, Microsystem Technologies, 24, 10, pp. 3995-4005, (2018)
  • [5] ZHU H Y, HAN C Z, HAN H, Et al., The algorithm and simulations for the asynchronous track association[J], Journal of System Simulation, 4, pp. 685-688, (2004)
  • [6] WANG C, WANG H P, XIONG W, Et al., Data association algorithm based on least square fitting, Acta Aeronautica et Astronautica Sinica, 37, 5, pp. 1603-1613, (2016)
  • [7] WU S J, MEI X C, Radar signal processing and data processing technology, (2008)
  • [8] CHENG C, Asynchronous multisensor track association algorithm and simulation, Procedia Environmental Sciences, 10, pp. 1109-1114, (2011)
  • [9] CUI Y Y, Local optimal bearing track correlation based on transform domain, Telecommunication Engineering, 56, 7, pp. 755-759, (2016)
  • [10] JIN B Y, LIU Z, QIN J K, Two-stage real-time track correlation algorithm based on gray correlation, Acta Armamentarii, 41, 7, pp. 1330-1338, (2020)
12