ISAR Image Registration Based on Normalized Correlation Coefficient

As an important part of attitude estimation for space target, the accuracy of ISAR image registration directly affects the result of attitude estimation. In this paper, we analyze the model of ISAR image registration and propose a novel method. First, the image is binarized to reduce the impact of echo SNR, and then the global normalized cross-correlation coefficient between the images is taken as the cost function to estimate the parameters with Snake Optimizer algorithm to achieve registration. The experiment proves the effectiveness of this method.