ISAR Imaging Phase Correction Algorithm Based on Entropy Minimization

In the present work, an Inverse Synthetic Aperture (ISAR) imaging technique with a phase correction is discussed. Based on discrete geometry of the observed object and linear frequency modulation (LFM) emitted waveform, an ISAR signal model is constructed. An iterative Range-Doppler image reconstruction algorithm with a phase correction of higher order is developed. It includes: signal demodulation and radial motion compensation of object's mass center; 2-D inverse Fourier transformations for image extraction, removing ISAR signal's phases of higher order on azimuth and range directions by multiplication with an exponential term with argument - a polynomial of a second order, and using entropy as an image cost function. The geometry, signal model and image reconstruction algorithm with a higher order signal's phase compensation are illustrated by numerical simulation experiments.