Asynchronous anti-bias track association algorithm by using k-nearest neighbors interval distance

被引：0
|
作者：
Yi X. [1 ]
Zeng R. [1 ,2 ]
Cao X. [1 ]
机构：
[1] School of Aviation Operations and Support, Naval Aviation University, Yantai
[2] Unit 92325 of the PLA, Datong
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2022年 / 44卷 / 05期
关键词：
Anti-bias association; Grey relational degree; Interval transform; K-nearest neighbors interval distance; Track association;
D O I：
10.12305/j.issn.1001-506X.2022.05.07
中图分类号：
学科分类号：
摘要：
To solve the problem of track association under the asynchronous and system error, an asynchronous anti-bias track association algorithm based on k-nearest neighbors interval distance of the track sequence is proposed. The k-nearest neighbors interval distance measurement between interval sequence and interval points is defined, the method of the system error interval is put forward, the grey relational degree among the sequences of different track intervals are calculated, and the classical allocation method is used to determine the track-to-track association. Compared with the traditional algorithms, the requirement for prior information on system bias is lower. The simulation results show that the algorithm can achieve stable association with a high accuracy, and good anti-bias performance. The algorithm can also deal with the asynchronous unequal rate track association problem without time domain registration, which has obvious advantages. © 2022, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：1475 / 1482
页数：7
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