Adaptive sequential track-association algorithm based on data quality assessment

被引：0

作者：

Zhang Y. ^{[1
]}

Wu K. ^{[2
]}

Guo J. ^{[1
]}

Ge Z. ^{[2
]}

Zhang B. ^{[1
]}

机构：

[1] School of Aerospace and Engineering, Beijing Institute of Technology, Beijing

[2] Shanghai Electromechanical Engineering Institute, Shanghai

来源：

Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2022年 / 44卷 / 11期

关键词：

data quality assessment; entropy method; fuzzy control; multi-source information fusion; track-association;

D O I：

10.12305/j.issn.1001-506X.2022.11.23

中图分类号：

学科分类号：

摘要：

In order to solve the track-association problem when sensor suffers declined accuracy, an adaptive sequential track-association algorithm based on data quality assessment is proposed. Real-time data quality evaluation results are introduced into the adjustment of correlation threshold. The entropy method and the utility function method are combined to evaluate the performance of sensor and the quality of filtering, and the fuzzy control relationship between two indexes and the significance level is constructed, so as to realize the adaptive adjustment of correlation threshold. The simulation results show that the performance of the improved algorithm is better than that of compared algorithm in the situation of declined sensor accuracy, and the good correlation effect is beneficial to the improvement of fusion accuracy. It also has good adaptability in the case of maneuver target tracking. © 2022 Chinese Institute of Electronics. All rights reserved.

引用

页码：3477 / 3485

页数：8