A motion-based integer ambiguity resolution method for attitude determination using the global positioning system (GPS)

Loss of the satellite signal and noise disturbance will cause cycle slips to occur in the carrier phase observation of the attitude determination system using the global positioning system (GPS), especially in the dynamic situation. Therefore, in order to reject the error by cycle slips, the integer ambiguity should be re-computed. A motion model-based Kalman predictor is used for the ambiguity re-computation in dynamic applications. This method utilizes the correct observation of the last step to predict the current ambiguities. With the baseline length as a constraint to reject invalid values, we can solve the current integer ambiguity and the attitude angles, by substituting the obtained ambiguities into the constrained LAMBDA method. Experimental results demonstrate that the proposed method is more efficient in the dynamic situation, which takes less time to obtain new fixed ambiguities with a higher mean success rate.