This book endeavours to give a concise contribution to understanding the data assimilation and
related methodologies. The mathematical concepts and related algorithms are fully presented
especially for those facing this theme for the first time. The first chapter gives a wide
overview of the data assimilation steps starting from Gauss' first methods to the most recent
as those developed under the Monte Carlo methods. The second chapter treats the representation
of the physical system as an ontological basis of the problem. The third chapter deals with the
classical Kalman filter while the fourth chapter deals with the advanced methods based on
recursive Bayesian Estimation. A special chapter the fifth deals with the possible
applications from the first Lorenz model passing trough the biology and medicine up to
planetary assimilation mainly on Mars. This book serves both teachers and college students
and other interested parties providing the algorithms and formulas to manage the data
assimilation everywhere a dynamic system is present.
