Data Assimilation: Mathematical Concepts and Instructive Examples
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"This is a very nice book for non-experts who would like to get into the area of data assimilation. The well-organized structure and the step-by-step introduction of the concepts with the help of illustrative examples also make it suitable as a textbook for graduate courses. ... A good amount of historical information and background material is included in this book ... . the book would be more appealing and provide direction to young researchers." (Nan Chen, Mathematical Reviews, March, 2016)
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 third chapter deals with the classical Kalman filter, while the fourth chapter deals with the advanced methods based on recursive Bayesian Estimation.