CHAFF JAMMING RECOGNITION BASED ON PULSE DOPPLER RADAR

In order to effectively combat the adverse effect of chaff jamming on ship detection by pulse Doppler radar, a chaff jamming recognition method based on range-Doppler image and deep target detection network is proposed in this paper. The chaff cloud diffusion model and the echo model of pulse Doppler radar are established, and the differences of two-dimensional range-Doppler images between ship target and chaff jamming echo are analysed. On this basis, convolutional neural network is utilized to extract the deep features of the image, and the classification and localization of chaff jamming are completed automatically. The performance of the model is verified by simulation and measured data. The results show that the proposed method can effectively solve the problem of chaff jamming recognition under high jamming to noise ratio, and the jamming range-Doppler information provided by the detection results is helpful for jamming suppression.