TARGET CLASSIFICATION WITH LOW-RESOLUTION RADARS BASED ON MULTIFRACTAL CORRELATION CHARACTERISTICS IN FRACTIONAL FOURIER DOMAIN

Due to the restrictions of low-resolution radar system and the influence of background clutter during the target detection, it is difficult to classify different kinds of low-resolution radar aircraft targets. In this paper, we propose a multifractal correlation method in the optimal fractional Fourier domain found by fractional Fourier transform (FrFT), in which we extract the multifractal correlation features of aircraft target echoes and do target identification combined with the support vector machine. The experimental results show that FrFT can enhance the multifractal correlation characteristics of aircraft target echoes; the multifractal correlation features extracted from the optimal fractional Fourier domain can effectively distinguish different types of aircraft; and the classification and recognition rates of the multifractal correlation method in the optimal fractional Fourier domain are higher than that of the multifractal correlation method in time domain and the multifractal method in the optimal fractional Fourier domain.