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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.