A computational Kronecker-core array algebra SAR raw data generation modeling system

This work presents a new methodology for a synthetic aperture radar (SAR) raw data generation modeling system based on fast and efficient computations of cross-ambiguity functions, acting as point target response functions, and multidimensional cyclic correlations of these functions with selected target reflectivity density functions. Computational Kronecker-core array (CKA) algebra, a branch of finite dimensional multilinear algebra, is utilized as a tool for the analysis, design, implementation and modification of multidimensional fast Fourier transform (FFT) based algorithms for the efficient computation of the cross-ambiguity functions and the multidimensional cyclic correlation operations. A MATLAB/sup (R)/ environment was created for the implementation of the complete SAR raw data generation modeling system. A new DSP board based modeling system is currently being implemented for hardware in the loop simulations at the SAR data receiving facility of the University of Puerto Rico.