1. A method of estimating the position of a target with a tracking system using a sequence of images, comprising: acquiring a multi-dimensional image from said tracking system for a time step t; normalizing said image to produce a normalized image, said normalized image having an intensity within a given range; super-sampling said normalized image with at least one sample rate to produce a super sampled image; classifying said normalized image into target and background pixel sets; determining at least one statistic of said pixel sets, said act of determining at least one statistic comprising: updating for a plurality of prior time steps a temporal mean and standard deviation from said normalized image; calculating from said temporal mean and standard deviation: (i) a target mean and standard deviation of all pixels in said target set, and (ii) a background mean and standard deviation of all pixels in said background set; scaling the target and background mean standard deviation by a factor; and setting minimum and maximum bounds on said means and standard deviations; smoothing a prior probability from a previous time step; shifting the prior probability to produce an updated prior probability; calculating a posterior probability using at least said updated prior probability; and extracting a position of said target for at least one time step using at least said posterior probability.