Jordi Barr

> Thought, consider adaptive methods for sensor control to optimize power levels/clutter level, etc. Assume this may be possible in the optimiser. Yes, I think the optimiser should be able...

> I think it would be good to replace `StatePrediction` with `Track`, as then you'll have access to the entire track history, and track meta data. I can imagine use...

>  > > > I think it would be good to replace `StatePrediction` with `Track`, as then you'll have access to the entire track history, and track meta...

Branch created: https://github.com/dstl/Stone-Soup/tree/sensor_manager

And what would you do for off-diagonal elements?

Agree it would be worthwhile adding a line to the Kalman filter tutorial where the prior covariance ($P_0$) is first introduced.

+1 for OP, +1 for note of caution. Whilst inferring backward in time is useful for out-of-sequence and track stitching, it's not strictly 'prediction' (retrodiction perhaps?). The physicist part of...

> Looks good 👍 Just some minor formatting changes, undo changes that'll break NumPy 2.0 compatibility, and new additional `prior` for Prediction type. Don't think I did any of these...

I'm not in favour of adding 'measurement uncertainty'. I think it conflates measurement -- a realisation of a sensing action -- with measurement model uncertainty. A single measurement is a...

> @jmbarr I think the piece you are missing is that sometimes the uncertainty of a sensor is not constant. > No, I understand this perfectly well. Stone Soup, with...