Nonlinear Filter Evaluation for Estimating Vehicle Position and Velocity Using Satellites

Approximate nonlinear filtering theory is applied to the estimation of vehicle position and velocity in three demensions using sequential range measurements to three known locations. The particular case studied is a satellite air traffic control system which utilizes range measurements to two geostationary satellites and an altitude measurement. Three approximate filters are examined as suboptimal realizations of the minimum-variance filter and simulation results are presented to show that simple first-order approximation is an adequate representation. The parametric relationship between state covariance, measurement noise, vehicle maneuver structure, data rate, and system geometry is presented.