Suppression of Ionospheric Clutter for HFSWR Based on Neural Network

High frequency surface wave radar as a modern ocean detection and monitoring of remote sensing in the field of one of the main new technologies, vertical polarization antenna radiation electromagnetic waves, the use of high frequency band (3~ 30MHz) electromagnetic waves to achieve the conductive sea level bypass propagation, propagation attenuation is small and fast, can be achieved in all-weather time to achieve ultra-long-distance sea wide-area detection. In practical engineering applications of radar, there are a variety of clutter interference, and ionospheric clutter often seriously affects the detection performance of radar, so this thesis will start from the characteristics of ionospheric clutter of high-frequency surface wave radar, combined with neural networks, establish a model of ionospheric clutter, so as to achieve the suppression of ionospheric clutter.