Huge +1 for Roger Labbe's book/jupyter notebooks. They really helped me grok Kalman filters but also the more general problem and the various approaches that approximate the general problem from different directions.

That's a fair question. My goal with the site was to make as much material available for free as possible, and the core linear Kalman filter content is indeed freely accessible.

The book goes further into topics like tuning, practical design considerations, common pitfalls, and additional examples. But there are definitely many good free resources out there, including the one you linked.

i haven't seen much from other kalman filter resources, but i can say that this book is incredibly detailed and i would highly recommend it

if you dont want to buy the book, most of the linear kalman filter stuff is available for free: https://kalmanfilter.net/kalman-filter-tutorial.html