earticle

영어

For the situation with unknown qualities of local tracks in 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 of a moving target in adjacent interval transmitted by the 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 fusion without the prior information of local tracks. The experimental result illustrates that the proposed method can 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 in accuracy compared with the traditional methods.