Cross-range Scaling for ISAR with Short Aperture Data

Inverse Synthetic Aperture Radar (ISAR) imaging in short coherent processing interval has a great deal of major advantages in application. In this paper, a novel cross-range scaling algorithm for ISAR imaging with limited pulses and short aperture is proposed. Based on the sparsity characteristic of ISAR image, superresolution ISAR imaging can be achieved via Compressive Sensing (CS) theory. Then the Rotation Angle Velocity (RAV) estimation is realized by using 2-D Fast Fourier Transform (2-D FFT) and polar mapping. Meanwhile, the precision of RAV estimation can efficiently be improved by using CS. Finally, the ISAR image is properly rescaled in the range-cross-range domain. Both simulated and real-measured data experimental results confirm the effectiveness of the proposed method.