An Electromagnetic Target Classification Method for the Target Sets with Alien Target: Application to Small-scale Aircraft Targets

Abstract

The electromagnetic target classiflcation is a challenging problem since the scat- tered fleld from a target is highly dependent on operating frequency, polarization and aspect angle. In order to minimize adverse efiects of these dependencies an intelligent classifler con- taining some distinguishable target features is needed. In addition, in order to be suitable for real target applications, the properties of operating with moderate frequency bandwidth and discriminating an alien target from a target set containing friend targets are important. In this study, an electromagnetic target classiflcation method for isolated targets using noisy data in the classifler design to obtain high accuracy performance in a wider SNR range and having the ability of discrimination of an alien target without any priori information is introduced. The proposed method is mainly based on a late-time resonance region target classiflcation technique, which was reported recently to use the multiple signal classiflcation (MUSIC) algorithm and natural-resonance mechanism modeled by singularity expansion method (SEM) for target fea- ture extraction, and modifled for target sets containing alien target(s). The proposed classifler design method is demonstrated and tested for a target set of flve friend and one alien small-scale aircraft targets. According to the test result, the proposed method gives high accuracy rates for this target set.