海军航空工程学院学报2017，Vol.32Issue(2)：192-198,7.DOI:10.7682/j.issn.1673-1522.2017.02.003
基于多信息加权融合的降维航迹关联算法
Low Dimension Track Correlation Algorithm Based on Multi-Source Information Weighted Fusion
王通1
作者信息
- 1. 昆明理工大学管理与经济学院,昆明650000
- 折叠
摘要
Abstract
Low dimension track correlation algorithm was proposed to solve the high cost and long time problem of track correlation algorithm which aimed at distributed three sensors multi-target. This algorithm used, first of all, the estimated point of the two sensors'target position to construct the cost matrix of track correlation, to obtain the optimal solution;then reused this optimal solution and the estimated point of the third sensor's target position to construct the cost matrix of track correlation, to further obtain the three-dimension track correlation pairing. To solve the instability problem of single information source, in this paper, the algorithm of multi-information weighted fusion. This algorithm used the entropy weight method giving weight to information of various weighted fusion was proposed, transforming multi-information issue into single information issue. The simulation results showed that the new algorithm proposed in this paper not only reduced the tracking error of the target but also spent less time, demonstrating the effectiveness of the new algorithm.关键词
多源信息融合/熵权法/降维/航迹关联Key words
multi-source information fusion/entropy weight method/low dimension/track correlation分类
航空航天引用本文复制引用
王通..基于多信息加权融合的降维航迹关联算法[J].海军航空工程学院学报,2017,32(2):192-198,7.
