期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：10
页码：151-160
出版社：SERSC
摘要：For the situation with unknown qualities of local tracksin sensor networks, a new tracklet-global track fusion method using the support degree function (SDF-T2GTF) is proposed. According to the characteristic of actual transmission modes, two local estimates ofa moving target in adjacentinterval transmitted bythe same local node are defined as a tracklet, and subsequently tracklet-global track (T2GT) fusion can replace the traditional track fusion in the global node, namely local track-global track (LT2GT) fusion. Considered the advantage of the fuzzy track association (TA) method for unknown prior information of local tracks, it is used in T2GT association. Then all correlated tracklets in the same interval can be mapped into a set of points in parameter space by the Hough transform (HT) algorithm. The support degree function of these points is utilized to dynamically estimate the qualities of tracklets and reasonably allocates the weights of local estimates in fusion results. Hence, the proposed method can realize T2GT fusionwithout the prior information of local tracks. The experimental result illustratesthat the proposed methodcan satisfy the requirement of data transmission in real systems, and can realize T2GT fusion; on the other, it can improve the performance of track fusion inaccuracy compared with the traditional methods.
