It's bread and butter math for physics, Engineering (trad. Engineering), Geophysics, Signal processing etc.
Why would anyone have people implementing Kalman filters who found the math behind them "esoteric"?
Back in the day, in my wet behind the ears phase, my first time implementing a Kalman Filter from scratch, the application was to perform magnetic heading normalisation for on mag data from an airborne geophysical survey - 3 axis nanotesla sensor inputs on each wing and tail boom requiring a per survey calibration pattern to normalise the readings over a fixed location regardless of heading.
This was buried as part of a suite requiring calculation of the geomagnetic reference field (a big paramaterised spherical harmonic equation), upward, downward and reduce to pole continuations of magnetic field equations, raw GPS post processing corrections, etc.
where "etc" goes on for a shelf full of books with a dense chunk of applied mathematics
Why would anyone have people implementing Kalman filters who found the math behind them "esoteric"?
Back in the day, in my wet behind the ears phase, my first time implementing a Kalman Filter from scratch, the application was to perform magnetic heading normalisation for on mag data from an airborne geophysical survey - 3 axis nanotesla sensor inputs on each wing and tail boom requiring a per survey calibration pattern to normalise the readings over a fixed location regardless of heading.
This was buried as part of a suite requiring calculation of the geomagnetic reference field (a big paramaterised spherical harmonic equation), upward, downward and reduce to pole continuations of magnetic field equations, raw GPS post processing corrections, etc.
where "etc" goes on for a shelf full of books with a dense chunk of applied mathematics