Stochastic model of complex ISAR signals and spatial correlation image reconstruction procedure

Summary form only given. Inverse aperture synthesis is a process of collecting signal returns from a moving target illuminated by wide band transmitted pulses. This work deals with a stochastic model of signal returns and spatial correlation image reconstruction method for signal processing in inverse synthetic aperture radar (ISAR). Any hypothetic 2-D object flying within the ISAR range is depicted in a 3-D Cartesian grid by point scatterers placed at each node of the grid. The intensities of the point scatterers which belong to the object are described by applying stochastic process with Rayleigh probability distribution. The additive noise in the signal returns is modeled using Gaussian delta correlated zero mean process. The phases of the signals reflected by the point scatterers of the object are expressed by means of a stochastic uniform distribution process. The analytical expressions describing deterministic 3-D quadrature components of the ISAR signal returns are derived. A spatial correlation image reconstruction procedure, based on an analytic geometric approach in inverse aperture synthesis, is developed. Numerical experiments were performed. Complex microwave holograms and reconstructed images with different signal/noise ratio are obtained.