GEO 616E - State Mod.Kalman Filt.&Smooth.

Course Objectives

To teach students;
1.Use of Kalman Filtering with satellite based positioning systems
2.Mathematical models of Kalman Filtering
3.Engineering applications of Kalman Filtering

Course Description

Introduction, dynamic modeling, advantages and limitations. Models of geodetic measurement processes and empirical model identification. Linear or non-linear dynamic systems, transition matrix, observability and controllability, error propagation. Examples from kinematic positioning. Discrete optimal prediction, linear filtering and smoothing. Kalman filter, UD factorization, SRIF algorithm. Selected topics in nonlinear estimation. The extended & adaptive Kalman filter.