Howtosignalprocessing
- What is particle filter algorithm?
- Is a particle filter a Kalman filter?
- Is particle filter a Bayesian?
What is particle filter algorithm?
The particle filter is a Bayesian filter. This means, estimation is performed using Bayesian theory. Bayesian inference allows for estimating a state by combining a statistical model for a measurement (likelihood) with a prior probability using Bayes' theorem.
Is a particle filter a Kalman filter?
The Kalman and Particle filters are algorithms that recursively update an estimate of the state and find the innovations driving a stochastic process given a sequence of observations. The Kalman filter accomplishes this goal by linear projections, while the Particle filter does so by a sequential Monte Carlo method.
Is particle filter a Bayesian?
Bayes Filtering is the general term used to discuss the method of using a predict/update cycle to estimate the state of a dynamical system from sensor measurements. As mentioned, two types of Bayes Filters are Kalman filters and particle filters.
