I am trying to find a Kalman filter implementation which does not make the assumption that each observation is equally spaced and of equal weight. In particular, I have measurements of a process where I have a good estimate of how much evolution/elapsed-time the process has undergone between observations, but all the freely available Kalman filter code I have found offers no way to use this information.
The closest I have found is https://github.com/MathYourLife/Matlab-Tools/tree/master/kf_nonuniform_timestep but I think it still seems to weight multiple simultaneous observations higher than a single point estimate, which I am trying to avoid.