In this paper, the radar target recognition is given by frequency-diversity RCS (radar cross section) together with kernel scatter difference discrimination. The frequency-diversity technique means to collect electromagnetic signals by sweeping the operation frequencies. Such a technique is usually utilized in inverse scattering and radar target recognition because different frequencies each may contain important information of a target. By using the frequency diversity RCS technique, one can reduce the times of spatial measurement. This is an important contribution since it is always difficult to build a spatial radar measurement in practical battlefield environments. To enhance the pattern recognition, the collected RCS data are processed by the kernel scatter difference discrimination, which is improved from the Fisher discrimination. To investigate the capability of tolerating environmental fluctuation, each simulated RCS data is added by a random component prior to implementing pattern recognition. Numerical simulation shows that our recognition scheme is still very accurate even though the RCS contains a random component.
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