Application of nonlinear Kalman filter approach in dynamic GPS-based attitude determination

In this paper, nonlinear Kalman filter technique is applied to dynamic GPS-based attitude determination. The governing equation that characterizes the attitude information and GPS measurements is developed. A nonlinear Kalman filter algorithm is then formulated to estimate attitude, angular rate, integer ambiguity, and other relevant parameters. An experiment which uses a rotating mechanism platform to emulate a spin-stabilized satellite and two GPS carrier phase receivers to provide measurement data is conducted in this work to assess the feasibility of the proposed algorithm.