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Here's a survey that covers all of Bayesian filtering in 60 pages, plus references.

https://www.researchgate.net/publication/238689222






That's a nice survey. However for kalman filters it doesn't give practical examples or the different techniques to estimate the parameters. It doesn't cover adaptive modifications to kalmans like you often want in robotics or other applications to handle non-process external events which kalmans don't handle well. Et cetera, there's lots of reasons book forms on a topic can be useful.



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