Fn. Chowdhury, KALMAN FILTER WITH HYPOTHESIS-TESTING - A TOOL FOR ESTIMATING UNCERTAIN PARAMETERS, Circuits, systems, and signal processing, 15(3), 1996, pp. 291-311
In this paper we present a simple and practical algorithm for the esti
mation of uncertain parameters of linear systems. The uncertainty is t
wofold, involving random observation noise, and possible jumps in the
parameter values. The jumps may occur at unknown points in time, and a
re of unknown magnitudes and directions. The algorithm is based on the
Kalman filter, with a single-sample hypothesis test, which is used to
employ a three-state decision rule (yes, no, maybe). The ''maybe'' ch
oice invokes a fading memory Kalman filter. The overall algorithm cont
ains the constant parameter filter, fading memory filter, and the set
of tests and rules that enable it to switch back and forth between the
two filters. Application examples are presented.