Distributed track fusion algorithm based on inverse covariance crossover

被引：0
|
作者：
Du D. [1 ]
Li L. [1 ]
Yuan S. [1 ]
机构：
[1] Navy Research Institute, Beijing
来源：
Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University | 2022年 / 43卷 / 10期
关键词：
data correlation; data fusion; distributed track; ellipsoid method; Hellinger distance; inverse covariance crossover; root mean square error; track fusion evaluation index;
D O I：
10.11990/jheu.202110070
中图分类号：
学科分类号：
摘要：
In view of the unknown data correlation in track fusion, this paper first studies the preprocessing method of track fusion and realizes the coordinate conversion from local track to global track and the time alignment between tracks. Then, the distributed track fusion algorithm based on inverse covariance crossover is studied. The performance of the algorithm is analyzed comprehensively and fairly by using the track fusion evaluation index combined with the root mean square error, the state covariance matrix, and the Hellinger distance, thereby avoiding the limitation of a single index. Through theoretical analysis and computer simulation, the effectiveness of this algorithm is verified through a comparison with the covariance crossover algorithm, and the rationality of the evaluation index of the proposed track fusion is also verified. © 2022 Editorial Board of Journal of Harbin Engineering. All rights reserved.
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页码：1440 / 1446+1490
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