Focusses on filtering for linear processes, and helps design linear stable unbiased filters that yield an estimation error with the lowest root-mean-square (RMS) norm. This book defines various hierarchical classes of filtering problems based on the availability of statistical knowledge regarding noise, disturbances, and other uncertainties.