Enhanced Range Alignment Using a Combination of a Polynomial and Gaussian Basis Functions

For the inverse synthetic aperture radar (ISAR) imaging of a target at a long range, range alignment using the existing polynomial method brings about poor results because the flight trajectory changes depending on the initial position, and the motion parameters, meaning the polynomial cannot fit the trajectory. This paper proposes an improved range alignment method that models the trajectory using a combination of a polynomial and Gaussian basis functions. Initial parameters of the polynomial and Gaussian basis functions are determined by fitting the proposed model to the center of mass curve of the range profile history using the least square curve-fitting algorithm, and the optimum value is found using particle swarm optimization. This method is computationally more efficient and preserves the image quality.