Discussion
Which quantity does a Kalman filter propagate?
Answer: D
The Kalman filter keeps a Gaussian belief, updating its mean and covariance in closed form for linear dynamics with Gaussian noise. Under those assumptions it is exact and cheap. Sample populations belong to particle filters, discretised tables to grid filters, and a point estimate with an error bound is not a distribution. Knowing where its assumptions fail is what tells you when to reach for a particle filter instead.
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