Title :
Linear manifold constrained GLR
Author :
Liu, Jack S H ; Jones, Harold L.
Author_Institution :
Dynamics Research Corporation, Wilmington, MA, USA
fDate :
12/1/1977 12:00:00 AM
Abstract :
The Generalized Likelihood Ratio (GLR) algorithm has been developed to detect and identify state jumps [1]. Heretofore, the algorithm has been applied when: 1) the jump can be an arbitrary linear combination of states, or 2) the jump is one state. This correspondence describes the GLR application to the situation of state jumps constrained to lie among a fixed subset of states, a linear manifold.
Keywords :
Fault diagnosis; Jump processes; Linear systems, stochastic discrete-time; Signal detection; State estimation; Adaptive filters; Covariance matrix; Feedback; Kalman filters; Least squares approximation; Noise reduction; Parameter estimation; State estimation; Stochastic systems; White noise;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1977.1101663
