Gauss quadrature estimators

This paper presents an alternative method in dealing with nonlinear estimation problems. The principle is to approximate the integration of the conditional densities by using Gauss quadrature formulas and to set up the grid for the current filtering density simultaneously. The grid is centered at the filtering mean. The region where the grid locates is changed according to the conditional distribution. Approximation errors which depend on the choice of the number of nodes and the integration interval are discussed. Numerical experiments indicate that approximation errors do not accumulate during updating procedures.