I would recommend the old book by Gelb (see the first link below). It contains very useful intuitive considerations and engineering examples, though it does not cover some modern topics in optimal filtering.

A more modern survey is given by Simon (see the second link below). This book is wider in its scope but not so deep at the intuitive level of understanding.

As for me, I studied optimal filtering with applications to navigation using the book by Salychev (see the third link below). It is very controversial but thought-provoking. 

http://www.amazon.com/Applied-Estimation-Analytic-Sciences-Corporation/dp/0262570483

http://www.amazon.com/Optimal-State-Estimation-Nonlinear-Approaches/dp/0471708585/ref=asap_bc?ie=UTF8

http://www.amazon.com/Applied-Inertial-Navigation-Problems-Solutions/dp/5703823951/ref=asap_bc?ie=UTF8

Try this PhD thesis and the references given.

https://www.google.co.uk/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0ahUKEwicqfXI9tvKAhVBig8KHVSEChoQFgglMAA&url=https%3A%2F%2Fdspace.lib.cranfield.ac.uk%2Fbitstream%2F1826%2F2703%2F1%2FM%2520J%2520PROVOST%2520THESIS.pdf&usg=AFQjCNHckwpFHXwYTB5Tw806AHsMHh_d7w&sig2=OOJMZOZkAPWsHcBtjz8yRg&cad=rja

Best Regards

Paul

I think this book can help you a lot. This book even contains exercises and solutions. Using Jupyter Notebook you can also practice Python coding while reading. 

https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python 

I found  the reference below interesting. It developed the Kalman filter parameters tuning in chapter 6, have a look: 

Authors: R Doraiswami, M Stevenson and C Diduch 

Identification of Physical Systems: Applications to Condition Monitoring, Fault Diagnosis, Soft Sensor and Controller Design (2014)Publisher: Wiley Blackwell, Pages: 1-512

ISBN: 9781118536483 (ISBN); 9781119990123 (ISBN)

DOI: 10.1002/9781118536483

Optimal Filtering, by Anderson and Moore is old, but excellent. It doesn't describe the 'ensemble KF', but starts from first principles.  You'll have a clear mathematical foundation from this book.

At Amazon:  http://www.amazon.com/Optimal-Filtering-Dover-Electrical-Engineering/dp/0486439380

http://www.amazon.com/Optimal-State...s/dp/0471708585/ref=asap_bc?ie=UTF8

Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches: Dan Simon: 

I recommend this book, in which Kalman filter is introduced detailedly at the second part.

I found following book very useful in understanding the crux of Kalman filtering with intuitions.

“Fundamentals of Kalman Filtering—A Practical Approach By Paul Zarchan”

In this Book you can find a number of, detailed, real-world examples, elucidating the methodologies in which Kalman filters can be designed and implemented.

Kalman Filtering and Neural Networks

Editors: Simon S. Haykin

From the point of view of theoretical background and practical application I can recommend the following book: M.S. Grewal, A.P. Andrews. Kalman Filtering. Theory and Practice. Prentice Hall, 1993, 381 p.

I do recommend three book by my preference and very intuition that they would give you.

1. The very old book of Gelb "Applied Optimal Estimation" which is the very reference I go back to in case i want something concrete.

2. "Optimal Filtering", by Anderson and Moore is also a great book and you should consider reading it.

3. If you want to read a new book which also has a touch on programming you could take a look at  "Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches" by Dan Simon, where he also goes further by introducing some of the nonlinear approaches for nonlinear systems.

Hi, I hope that you've found some good KF references by now. I'd also go with Anderson and Moore as informative and affordable classic. Furthermore, you can find an introduction to the ensemble KF for researchers with a signal processing background on my profile.

1. M.S. Grewall, A.P.Andrews. Kalman Filtering. Theory and Practice. Prentice Hall, 1993.

2. H.W. Sorenson, ed., Kalman Filtering.Theory and Application. IEEE Press, 1985.

3. B.D.O. Anderson, J.B. Moore. Optimal filtering. Prentice Hall, 1979.

M.S. Grewall, A.P.Andrews. Kalman Filtering. Theory and Practice. Prentice Hall, 1993

A wonderful book for absolute beginners : Kalman Filter for Beginners with MATLAB examples by Phil Kim.

One good resource is kalmanfilter.net which explains KF from scratch to multi-dimensional models with worked out examples.

M.S. Grewall, A.P.Andrews. Kalman Filtering. Theory and Practice. Prentice Hall, 1993. Another for usual practice is 'Dan Simon codes'