Title :
Estimation and detection of signals in multiplicative noise
Author_Institution :
Massachusetts Institute of Technology, Cambridge, Massachusetts
Abstract :
We define a class of detection-estimation problems on matrix Lie groups in which the observation noise is multiplicative in nature. By examining the differential versions of the hypotheses, which are bilinear, we are able to derive the relevant likelihood ratio formula and the associated optimal estimation equations for the signal given the observations and the assumption that the signal is present. These estimation equations are of interest in their own right, in that they represent a finite dimensional optimal solution to a nonlinear estimation problem and consist of a Kalman-Bucy filter along with the on-line computation of the solution of the associated Riccati equation, which is driven by the observations. The usefulness of these results is illustrated via an example concerning the detection of an actuator failure in a rigid body rotational control system.
Keywords :
Additive noise; Algebra; Noise generators; Nonlinear equations; Nonlinear filters; Optical noise; Riccati equations; Signal detection; Signal generators; Signal processing;
Conference_Titel :
Decision and Control including the 13th Symposium on Adaptive Processes, 1974 IEEE Conference on
Conference_Location :
Phoenix, AZ, USA
DOI :
10.1109/CDC.1974.270530