Title :
Robust estimation with unknown noise statistics
Author :
Z.M. Durovic;B.D. Kovacevic
Author_Institution :
Fac. of Electr. Eng., Belgrade Univ., Serbia
Abstract :
The equivalence between the Kalman filter and a particular least squares regression problem is established and the regression problem is solved robustly using a statistical approach, named M-estimation. M-robust estimators are derived for adaptive estimation of the unknown a priori state and observation noise statistics simultaneously with the system states. The feasibility of the approach is demonstrated with simulation.
Keywords :
"Noise robustness","Statistics","Least squares approximation","State estimation","Gaussian noise","Adaptive estimation","Noise generators","Adaptive filters","Estimation theory","Probability distribution"
Journal_Title :
IEEE Transactions on Automatic Control
