Due to the limitations of low-resolution radar system and background clutter, the task of target classification with conventional low-resolution radars is relatively difficult. This paper introduces fractional Fourier transform (FrFT) to process aircraft echoes in order to find the optimal fractional Fourier domain, in which signal to noise ratio can reach the maximum, and then applies multifractal theory to the feature extraction of radar targets. Based on the above, we use SVM to do target classification. Experiments show that the multifractal characteristics of aircraft echoes can be enhanced by FrFT, and the features extracted from the optimal fractional Fourier domain can be used effectively to classify different types of aircraft even in the case of low SNR.

In the field of millimeter wave communication, antenna subset modulation (ASM) is widely known as a low-complex physical layer secure technology. However, the randomly selected antenna subset, may produce severe pedestal secondary lobes. In this letter, an enhanced ASM scheme, simulated annealing based orthogonal matching pursuit (SA-OMP), is proposed. In this idea, the transmit array is initially formulated by SA to implement secure transmission, on the basis of which the receive array can be determined by solving an overdetermined problem with OMP. Hence an equivalent pattern with low sidelobes is derived. Simulation results demonstrate the availability of the proposed approach.