Question on the update step of Bayesian filter

1. What are the two significant stages of the Bayesian filter?
2. What happens if at any point in Bayesian filtering the probability of a state assignment becomes 1?
3. How does Bayesian filtering work?
4. Are Kalman filters Bayesian?

What are the two significant stages of the Bayesian filter?

Using the recursive equation there are two general steps for a Bayes filter, the prediction and correction steps.

What happens if at any point in Bayesian filtering the probability of a state assignment becomes 1?

If at any point one of the buckets of the Bayes filters reaches 0 or 1 after normalization then the Bayes filter will become overconfident in its state and not allow for some future belief which may include the actual state of the robot.

How does Bayesian filtering work?

A Bayesian filter works by comparing your incoming email with a database of emails, which are categorised into 'spam' and 'not spam'. Bayes' theorem is used to learn from these prior messages. Then, the filter can calculate a spam probability score against each new message entering your inbox.

Are Kalman filters Bayesian?

Kalman filter is the analytical implementation of Bayesian filtering recursions for linear Gaussian state space models. For this model class the filtering density can be tracked in terms of finite-dimensional sufficient statistics which do not grow in time∗.