Title :
Tracking Aided Target Identification Based on Evidence Theory Data Mining
Author :
Hongfeng, Wang ; Ganlin, Shan ; Lu, Gao
Abstract :
To improve the precision of target attribute identification, a kind of tracking aided target identification method based on evidence theory data mining is advanced in this paper. Tracking information is imported to attribute fusion, thus improve the performance and accuracy of target identification. The experiment result proves the validity of this method. Especially when there are little sensors of attribute measurement, this method is more practical.
Keywords :
belief maintenance; data mining; sensor fusion; signal classification; target tracking; attribute fusion; attribute measurement; belief functions; data mining; evidence theory; target attribute identification; tracking aided target identification; tracking information; Bayesian methods; Boolean algebra; Data mining; Educational institutions; Equations; Instruments; Mechanical engineering; Sensor phenomena and characterization; Target tracking; Upper bound; data mining; evidence theory; target identification;
Conference_Titel :
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-1136-8
Electronic_ISBN :
978-1-4244-1136-8
DOI :
10.1109/ICEMI.2007.4351074
