Fourier series and estimation: An application to optical phase tracking

Methods of Fourier analysis and an assumed folded normal density approximation are applied to a nonlinear estimation problem in which the observation consists of a doubly stochastic Poisson process. A particular application to optical phase tracking is discussed. The performance, as computed by Monte Carlo simulation, of the resulting suboptimal estimator compares favorably to that of the "quasi-optimum" estimator of Snyder.