The strength of this book is the focus on the simplest state space model and then showing all the aspects of Kalman Filter framework and related pseudo-codes for filtering, smoothing. The novelty of this book is the central focus on the idea of orthogonalization of observation data. This makes all the Kalman Filter related formulae take convenient forms that one can intuitively as well as rigorously understand. One thing missing from this book is the discussion of numerical stability of filtering and smoothing algorithms, considering that the purpose of the book is to enable the reader code up his/her own KF functions.
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