ISAR Autofocus Using Rényi Entropy Minimization

Inverse synthetic aperture radar (ISAR) imaging generates two-dimensional target images by coherently processing radar cross-section data reflected from the target. During ISAR image formation, phase error correction in the Doppler direction is critical due to target motion. This paper presents a phase correction method based on the minimization of Rényi entropy, referred to as minimum Rényi entropy phase adjustment. The proposed approach estimates phase errors by differentiating Rényi entropy with respect to the phase error component and applying a fixed-point iteration scheme, producing high-resolution, well-focused ISAR images. Furthermore, the effect of the order parameter α in Rényi entropy is investigated by analyzing entropy as an image quality metric to determine its optimal value. The effectiveness of the proposed method is demonstrated using simulated ISAR signals from point scatterer models corrupted with phase errors.