ISAR cross-range scaling using principal component analysis and exhaustive search algorithm

摘要

The rotational velocity (RV) of a target is important for inverse synthetic aperture radar (ISAR) imaging, and must be known in order to rescale ISAR images from the range-Doppler domain to the homogeneous range-cross-range domain. In this paper, we propose a novel cross-range scaling technique for estimating the correct RV from ISAR images. This method involves two steps. First, it needs to extract the locations of high-energy scattering centers from two sequential ISAR images. Second, the proposed method utilizes an exhaustive search to estimate the correct RV of two-dimensional (2D) ISAR images using principal component analysis (PCA) and an appropriate cost function. The proposed method has two main advantages: 1) it does not require information about the rotation center of the target, and 2) it can efficiently generate a well-rescaled 2D ISAR image within a very short time. We present experimental results to demonstrate the validity of the proposed method.