ISAR imaging of non-cooperative objects with non-uniform rotational motion

In this paper, we propose data-driven optimization techniques for enhancing the ISAR image reconstruction process. We utilize keystone formatting to compensate for the range cell migration caused by the rotational motion and the well-established technique based on time-frequency signal analysis for the ISAR image reconstruction. The proposed optimization method for the keystone formatting determines the optimal slow-time window for the operation by minimizing a loss function depending on the contrast of the sum envelope of the range compressed signal. The optimization procedure proposed for the Cohen's class time-frequency representation determines an optimal kernel function by maximizing the contrast of the intensity normalized ISAR image function. In addition, we utilize the time-frequency reassignment method to enhance the contrast of the ISAR image. The algorithms are illustrated with a numerical example, which indicates that our methodology can be used to increase the performance of the non-cooperative ISAR imaging process.