I was referring to Q and R by "diagonal covariance matrix". Forgot P was also a covariance matrix.
But ye, control theory was over my head in university so ... I might be more frustrated with how simple and nice PI-controllers and first order IIR filters are used in industry while we were butting our heads bloody against the wall in university.
Industry uses a lot of things. Including Kalman filters, they are actually pretty common.
It's true that a lot of industry problems can be solved by linear regression, simple filters, Gaussian distributions, etc. Which can make you wonder why you bothered about all that stuff in your degree - but it's also true that there are a lot of interesting problems in industry that just aren't amenable to the most basic approaches.
It's also true that for the most part, bashing your head on this stuff in university improved your ability to think about the problem spaces.
I think here you are confusing initialization of an estimator with the estimation process.