Wide Bandwidth ISAR Imaging and Cross-Range Scaling Via Modified Polar Format Algorithm

Inverse synthetic aperture radar (ISAR) is extensively used in space situational awareness, with its imaging resolution improving as signal bandwidth increases. However, high-order migration through range cell (MTRC) and phase errors due to target rotation can degrade image focus. Traditional algorithms model rotation as a polynomial to compensate for these errors, but this approach becomes computationally intensive and less accurate with higher bandwidths. Additionally, residual errors from previous compensation steps can accumulate, further reducing overall accuracy. In contrast, polar interpolation with actual rotation parameters can effectively compensate for MTRC and phase errors across all orders without the drawbacks of sequential compensation. Motivated by this point, this paper proposes a modified polar format algorithm (PFA) that establishes a link between ISAR imaging quality and effective rotation parameters. By applying the minimum entropy criterion, the algorithm iteratively refines and optimizes the estimation of these parameters, compensating for all MTRC and phase errors in a single step, thus ensuring high overall compensation accuracy. With the optimized parameters, the algorithm also achieves precise cross-range scaling in imaging results. Extensive experiments verify the effectiveness and superiority of this proposed algorithm compared with other existing methods.