Conference Proceedings
James-Stein state space filter
JH Manton, V Krishnamurthy, HV Poor
Proceedings of the IEEE Conference on Decision and Control | IEEE | Published : 1997
Abstract
In 1961, James and Stein discovered a remarkable estimator which dominates the maximum-likelihood estimate of the mean of a p-variate normal distribution, provided the dimension p is greater than two. This paper, by applying `James-Stein estimation theory', derives the James-Stein state filter (JSSF), which is a robust version of the Kalman filter. The JSSF is designed for situations where the parameters of the state-space evolution model are not known with any certainty.