Hi everyone,I am working on a kalman filtering problem,but i don't understand how this algorithm is being used for two dimensional tracking of the position variables.Unlike LMS,NLMS and RLS algorithm I couldn't figure out what's going on in this kalman filter as it is completely dependent on state equaions.If someone could explain this with an example I would appreciate it. thanks in advance regards, Mohan p.s:Let's say the position variables are assumed to be observed in noise and represented as a state equation how do we track the position variables? |