Title :
Air Target Classification in Two Dimensional Feature Space
Author :
Golmohammad, Hassan ; Bolandi, Hossein ; Saberi, Farhad Fani
Author_Institution :
Iran Univ. of Sci. & Technol., Tehran
Abstract :
Results of two classifier is combined to make more reliable decision about the type of airplanes. Two classifiers are maximum acceleration classifier, which is implemented as an IMM filter, and maximum speed classifier which is a classical Bayesian classifier. Since TBM in data fusion applications is a cautious algorithm, it is adopted for this purpose. Finally, Monte Carlo simulation was carried out to show the efficiency of proposed approach.
Keywords :
Bayes methods; Monte Carlo methods; aerospace computing; filtering theory; sensor fusion; signal classification; target tracking; Bayesian classifier; IMM filter; Monte Carlo simulation; air target classification; airplane classification; data fusion; maximum acceleration classifier; maximum speed classifier; Acceleration; Data mining; Feature extraction; Intelligent sensors; Sensor fusion; Sensor phenomena and characterization; Sensor systems and applications; Space technology; Surveillance; Target tracking;
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
DOI :
10.1109/ICIT.2006.372312
