Abstract
The Schmidt Kalman Filter is presented in this study for float ambiguity resolution and attitude estimation of a multi-antenna platform using single-frequency GNSS measurements. The geometry information of the antenna configuration is fully exploited for ambiguity resolution via formulating the direct functional relationship between double-differenced carrier phase measurements and attitude quaternions. A first-order Gauss–Markov process is employed to model the remaining observation colour noise. The attitude parameters and the colored observation noise are decoupled in the state equation with Schmidt Kalman Filter. The Least-squares AMBiguity Decorrelation Adjustment (LAMBDA) algorithm is implemented for integer ambiguity resolution. The process of attitude determination algorithm via Schmidt-Kalman filter is designed and a static GNSS test is carried out to validate the filter performance. Results show that the Schmidt-Kalman filter performs better than the standard reduced-order Kalman filter and QUEST algorithm in terms of the integer ambiguity resolution (such as, the success rate and Time-to-Fix) and the accuracy of attitude angles for BDS, GPS and GPS + BDS. The double GNSS have better performance than single constellation, and there is no big difference between GPS and BDS for attitude determination.
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