Real-time kinematic positioning algorithm with GNSS and high-frequency accelerometer observations for broadband signals

Real-time kinematic (RTK) positioning technology is widely used for deformation monitoring, but the signals of high-frequency band such as velocity and acceleration are easily polluted due to the bad signal to noise ratio. In order to obtain high-precision and broadband signals for deformation monitoring, we propose an enhanced real-time kinematic (RTK) positioning algorithm by adding high-frequency accelerometer observations and estimate the bias of the acceleration as an unknown parameter in real-time. In addition, a dataset was constructed based on an experiment and used for the validation of our approach. The experiment is operated on a platform and includes a dynamic GNSS antenna, a low-cost Micro-Electro-Mechanical System (MEMS)-type accelerometer and a slide rail. We conducted eight simulations by sliding the collocated GNSS antenna and MEMS from one point to the other point by manual operation to record two dimensional movements in horizontal components. A vernier caliper was also set up to estimate the reference displacement for comparison, the maximum sliding distance of the platform is restricted to about 0.5 m. Our validation analyses demonstrate that the enhanced RTK positioning algorithm can provide high-precision displacement, velocity, and acceleration signals in real-time. The average accuracies are 5.0 mm, 0.6 mm/s and 1.0 mm/s2 respectively. Furthermore, the high-resolution acceleration signal from the MEMS is helpful to improve the RTK ambiguity resolution because the R-ratio (the ratio of the second minimum to the minimum quadratic form of residuals) values achieved by the new approach are much larger than the standard RTK approach.