4 ms·
Kalman filters are never going to completely go away since they are optimal[1] under certain assumptions. But these assumptions are often not met so you have to
by rawnlq 10y ago
Kalman filters are never going to completely go away since they are optimal[1] under certain assumptions. But these assumptions are often not met so you have to start approximating (with EKF or UKF).
In those scenarios, once computational power allows, I think other approaches such as particle filters which can handle arbitrary distributions(e.g., multimodal) will start taking over. But we're not there yet(?).
[1]https://en.wikipedia.org/wiki/Kalman_filter#Optimality_and_performance https://en.wikipedia.org/wiki/Kalman_filter#Optimality_and_p...
- kurthr 10y agoI agree both EKF and UKF are what you'll find in real world applications (because computing Jacobians is a pain!). I find the work of Jeffery Uhlmann both incredibly useful and hilarious (in that the "Unscented Kalman Filter" came from a stick of deodorant on a co-workers desk). http://ethw.org/First-Hand:The_Unscented_Transform http://ethw.org/First-Hand:The_Unscented_Transform