I think I finally arrived at a good ordering of material.
Started with implementing a linear problem just so we can
see how it differs from the linear KF, then added problems
step by step. Got rid of most of the poor performing filters.
I moved it more to the front as the pos vs velocity explanation
is difficult to understand if you do not already understand how
orthogonal or correlated measurements greatly increase precision.
Also various minor wording changes and fixes in other parts.
Position vs velocity confuses people, so I added a 2 position
reading example.
Fixed the Newtonian equation for jerk.
Changed indefinite integral in Newtonian equations to definite.
I wrote a chapter introducing the problem of nonlinearity in KF because this
information is common to the EKF, UKF, etc. Then I reordered chapters. I want
people ot learn the UKF before the EKF. While I was doing this, I moved the
H Infinity and Ensemble filters to later chapters because they are mostly
curiosities in this book.
The contents section is a pain to maintain, and it doesn't really
add anything of important. Maybe i'll add it back in once the book
is settled down, but probabl not.
My charts were mixing position vs time, which was pretty confusing.
I changed it to position vs velocity, and demonstrated how multipying
the covariances lead to a much better result.
I had a lot of problems with lines being visible, and ended up
using different styles in different places. I found a style that
seems to work everywhere and put the code in book_plots.py.
I had already explained that you cannot KF the output of a GPS
(this is extemely prevalent in hobbiest projects on the web).
But now I added an example in code of what happens when you try
this.
I moved book_format.py to the root directory so that all of the
notebooks do not need to modify the system path to import it. It
modifies the path on import so that all of the code in ./code can
then be accessed.
Altered links to nbviewer to account for no longer using subdirectories.
