Polynomial autocorrelation control for memoryless nonlinear transform

With the rising prominence of high-resolution high-grazing-angle radar, new distributions have come into use that prevent the application of techniques limited to the simulation of spherically invariant random processes. The use of the memoryless nonlinear transform for the simulation of KK-distributed clutter is considered. A truncated power series is used to control the autocorrelation of the resulting process, and its remainder is shown to diminish at worst exponentially with the order of approximation.