Abstract:

Stable and effective target feature extraction is very significant for target classification of low resolution radar. An approach to classify the radar target feature from the radar cross section (RCS) and spectral entropy probability distribution curves is proposed. The target spectrum calculation by the fast Fourier transform (FFT) is first used to obtain the target RCS and spectrum entropy. Then the probability distribution curves of the part basic features are calculated, and the stable target feature is extracted from the curves. The measured data results based on the support vector machine show the proposed feature can not only be robust to the target and achieve good classification performance, but also implement simply.