With the advancement of multi-GNSS systems, the field calibration of GNSS receiver antennas has been updated at Wuhan University. Benefiting from the use of a six-axis robot that can change its position and attitude precisely, multisession calibration experiments were implemented for several antennas of two types. The calibrations show a high stability of 1 mm for both the phase center offset and phase variation estimation. Compared to the models disclosed in igs14.atx and igsR3.atx, phase center correction differences at the 1 mm level can be obtained for most signals for elevation angles above 15°. For lower elevations, the consistency with the reference model increases to 2–3 mm or more. The consistency of calibrations with different receivers was investigated, and root mean square of differences between these models was better than 0.15 mm. In a short-baseline positioning experiment, the coordinate discrepancies introduced by an antenna phase center (APC) model between GPS and BDS-3 signals could be significantly reduced to the 1 mm level. Compared to the reference coordinates, the positioning accuracies for GPS and BDS-3 were both less than 2 mm with the adoption of the calibrated APC model. The multi-GNSS calibration system tested in this experiment is preliminarily proven reliable and could be applied to future antenna calibration for multi-GNSS applications.

GNSS attitude determination has been widely adopted due to its high efficiency, absence of cumulative errors, and ease of installation. However, practical navigation and attitude determination systems often rely on low-cost receivers that struggle with substantial multipath effects, frequent cycle slips, and satellite signal loss, significantly impairing attitude determination accuracy in challenging urban environments. To address this issue, this contribution proposes a constrained dynamic prediction model (C-Dynamics), which enables more accurate initial coordinates and thereby increases the effectiveness of the constrained LAMBDA (CLAMBDA) technique. To evaluate the practical performance of C-Dynamics, two sets of real-world data collected from a vehicle platform were analyzed. The results demonstrate that C-Dynamics significantly enhances the accuracy of initial coordinate estimations across various environments. Compared with the lambda method, the CLAMBDA method + C-Dynamics method (CLAMBDA+CD) improves the fixing rate in the urban environment by 5.6%, and the accuracy of the heading angle, pitch angle, and baseline length improved by 66%, 70.9%, and 84.2%, respectively. Moreover, in challenging high obstruction environments, the fixing rate increased by 43.5%, while the accuracy of heading angle, pitch angle, and baseline length improved by 76.4%, 69.2%, and 94%, respectively. The proposed algorithm effectively addresses the low fixing rate and insufficient accuracy of the LAMBDA method in high obstruction environments and holds practical value for widespread adoption in the mass market.