Isar Signal Modeling and Image Reconstruction with Entropy Minimization Autofocussing

In this work a model of deterministic components of ISAR trajectory signal with stepped frequency modulation based on 3D ISAR geometry is suggested. The object space, moving rectilinearly, is presented as a 3D regular grid of isotropic point scatterers. The analytical expressions for computing distances to each point scatterer of the object space are derived. The image reconstruction procedure includes both range and azimuth compression. Cross correlation technique and fast Fourier transform (FFT) to 2D ISAR signal map to realize range compression and azimuth compression, respectively are applied. An autofocusing technique based on entropy minimization is implemented to each ISAR return signal. In order to illustrate the capability of the ISAR signal model and verify the phase correction technique performed by entropy minimization numerical experiment is worked out