Modeling and simulation of point spread functions for advanced SAR systems

This work deals with the treatment of remotely sensed or sensory data in order to extract important information to the users. Sensory data are data collected from physical systems; by using sensors, such as the synthetic aperture radar (SAR) system. A fundamental stage in SAR processing is computation of its point spread function (PSF); necessary for raw data generation. The PSF contains the backscattered energy of a single point target on the Earth, allowing the extraction of surface information. The effort of this work is concentrated in the development of a mathematical model for PSF simulations and SAR raw data generation. The SAR impulse response is modeled in a time-frequency analysis context as the radar ambiguity function of a single point in the spatial object domain. The simulation algorithms were programmed using the functional programming style to get modularity. These algorithms were developed and tested in Matlab. The mathematical model was validated using a methodology based on theoretical formulations available in the literature. Simulations results demonstrated that not only the model is valid, but also the efficiency of the implemented algorithms as a tool for modeling and simulation of SAR impulse response functions.