Comparison of various static multiple-model estimation algorithms

A static multiple-model (SMM) estimation and decision algorithm has two functions: estimate the state of the system and decide which model is the best representation of the system. This paper concentrates on static multiple-model systems, that is, there is only one mathematical model applicable to a sequence of measurements, that model is one of a number of known possible mathematical models, but which one of these models is applicable is not known. In this paper, the characteristics of both estimation and decision errors of three SMM optimal algorithms are evaluated with a variety of performance measures using a Monte Carlo simulation.