A hidden Markov model (HMM)-based method for recognizing aerial targets according to the sequential high-range-resolution (HRR) radar signature is presented. Its recognition features are the location information of scattering centers extracted from the HRR radar echoes by the relax algorithm. The HMM is used to characterize the spatio-temporal information of a target. Several HMMs are cascaded in a chain to model the variation in the target orientation and used as classifiers. Computer simulations with the inverse synthetic aperture radar (ISAR) data are given to demonstrate that for an open-set recognition, average class-recognition rates of 84.50% and 89.88% are achieved, respectively, under two given conditions.
Multi-aspect radar target recognition method based on scattering centers and HMMs classifiers
IEEE Transactions on Aerospace and Electronic Systems ; 41 , 3 ; 1067-1074
2005-07-01
602867 byte
Article (Journal)
Electronic Resource
English
Radar Target Modeling and Recognition Based on Scattering Centers
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