Efficient Cross-Range Scaling Method via Two-Dimensional Unitary ESPRIT Scattering Center Extraction Algorithm

For a better understanding of the inverse synthetic aperture radar (ISAR) image, cross-range scaling is an essential step. To deal with the scaling problem of ISAR image, this letter proposes a novel cross-range scaling algorithm for ISAR image. This method consists of three steps. In the first step, joint time-frequency method is employed to compensate the rotational motion and generate 2-D ISAR images at two selected times. Theoretically, after rotating the angular shift between the two images, they present the same appearance. However, conventional image rotation is computationally inefficient and complex for implementation. Thus, in the second step, we propose a 2-D unitary estimation of parameters via rotation invariance technique (ESPRIT) superresolution ISAR imaging technique to extract isolated scatterers instead of conventional ISAR image. In the last step, we search rotation velocity (RV) and rotate the image by angular shift to find the right RV that makes the two selected images match each other best. Finally, simulated and real ISAR data are provided to demonstrate the effectiveness and correctness of the proposed cross-range scaling algorithm.