A GPS/INS Multiple Model Adaptive Kalman Filter for Carrier Phase Integer Ambiguity Resolution and Cycle Slip Detection

Walton R. Williamson and Jason L. Speyer

Abstract: In order to perform high accuracy, relative position, velocity and attitude estimation between two moving vehicles, a new algorithm, the Multiple Model Adaptive Kalman Filter (MMAKF) is proposed for integrating the carrier phase integer ambiguity resolution problem within the framework of a GPS/INS Differential Carrier Phase Extended Kalman Filter (DCP EKF). This algorithm does not assume the use of a base station to provide relative state corrections to either moving vehicles. The MMAKF algorithm is superior to other algorithms for three reasons. First, the algorithm uses the INS to aid the carrier phase estimation through the algorithms implementation with the GPS/INS DCP EKF. Second, the MMAKF possesses known convergence properties which guarantee convergence to the correct hypothesis. Finally, the algorithm is capable of detecting and repairing cycle slips. Test results presented in this paper show the response of this filter to cycle skips using actual GPS/INS data taken at UCLA.
Published in: Proceedings of the 2000 National Technical Meeting of The Institute of Navigation
January 26 - 28, 2000
Pacific Hotel Disneyland
Anaheim, CA
Pages: 115 - 124
Cite this article: Williamson, Walton R., Speyer, Jason L., "A GPS/INS Multiple Model Adaptive Kalman Filter for Carrier Phase Integer Ambiguity Resolution and Cycle Slip Detection," Proceedings of the 2000 National Technical Meeting of The Institute of Navigation, Anaheim, CA, January 2000, pp. 115-124.
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