Title :
Fuzzy Double-Threshold Track Association Algorithm Using Adaptive Threshold in Distributed Multisensor-Multitarget Tracking Systems
Author :
Wei Du ; Huansheng Ning ; Yuan Wei ; Jun Wang
Author_Institution :
Sch. of Electron. & Inf. Eng., Beihang Univ., Beijing, China
Abstract :
The fuzzy double-threshold track association algorithm using the adaptive threshold (AT-FDTTA) is presented in this paper. The AT-FDTTA is described in detail at first. Then, the simulations of two different cases are designed to illustrate the improved performance caused by the adaptive threshold. Both the simulation results show that the correct association rate of the AF-FDTTA proposed here is higher than that of the fuzzy double-threshold track association algorithm with the fixed threshold (FT-FDTTA) algorithm, Besides, the AT-FDTTA is with lower missing association rate. Moreover, the high performance of the AT-FDTTA is not sensitive to other parameter values in the algorithm, which are usually chosen empirically by the users.
Keywords :
distributed algorithms; fuzzy set theory; sensor fusion; signal detection; target tracking; AT-FDTTA; FT-FDTTA algorithm; adaptive threshold; distributed multisensor-multitarget tracking systems; fixed threshold algorithm; fuzzy double-threshold track association algorithm; missing association rate; Adaptive systems; Clustering algorithms; Internet; Logic gates; Target tracking; Vectors; adaptive threshold; fuzzy track association; track-to-track association;
Conference_Titel :
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location :
Beijing
DOI :
10.1109/GreenCom-iThings-CPSCom.2013.197