Recurrent Kalman Procedure for ISAR Image Reconstruction from Barcer’s Phase Code Modulated Trajectory Signals

This work presents an original approximate recurrent approach for image reconstruction from inverse synthetic aperture radar (ISAR) data, obtained by illuminating the target with Barcer’s phase code modulated transmitted signal. Geometrical model of ISAR scenario and mathematical expressions of quadrature components of ISAR signal with Barcer’s phase code modulation, reflected by object with a complex geometry, are derived. Approximation matrix functions are constructed and used for modeling deterministic ISAR signals reflected by point scatterers, located at nodes of a uniform grid (model) that is depicted in the object’s coordinate system. The computational equations of Kalman filtering procedure for target feature extraction from Barcer’s phase code modulated ISAR signal are described. To demonstrate the validity and correctness of the developed recurrent Kalman image extraction procedure, numerical experiment is performed. The computational results disclose the capability of the Kalman procedure to obtain high resolution images by short inverse synthetic aperture length, unambiguous and convergent estimates of the point scatterers’ intensities of a target from simulated ISAR data.