基于小波变换的序贯航迹关联算法

Algorithm for sequential track correlation based on wavelet transform

在分布式多传感器信息融合系统中,航迹关联是航迹融合过程中首要解决的问题,即如何判断来自于不同系统的航迹是否来源于同一目标.本文将小波变换引入到航迹关联算法研究中,利用小波变换将卡尔曼滤波后的航迹提取新的特征向量,从航迹的整体态势和局部细节变化两方面对原有的序贯航迹关联算法进行改进,提出了一种新的航迹关联算法.该算法将小波变换与序贯思想结合起来,提高了正确关联率.最后,对该算法进行仿真实验,证明了该算法的正确性和有效性,并搭建了数据链信息融合半实物仿真测试平台,模拟了数据链系统中信息融合的全过程.

In the distributed multi - sensors information fusion system, track correlation that aims to decide if the tracks from different system come from the same target is the key problem during the tracks fusion process. The theory of wavelet is inducted in the algorithm for track correlation in this paper. Based on sequential track correlation algorithm, a new kind of track correlation algorithm is proposed. This new algorithm can judge the tracks correlation from the whole trend and the detailed movement of tracks by extracting the new characteristic vector of tracks depended on wavelet transform after the tracks have been filtered by Kalman filter. The combination of wavelet transform and sequential concept could provide more precise correlation. At the end of the article, the simulation results show the new algorithm is correct and effective. Furthermore, the test platform is built for simulating the whole process of information fusion.