Adaptive non-holonomic constraint aiding Multi-GNSS PPP/INS tightly coupled navigation in the urban environment

The non-holonomic constraint (NHC) is a classical motion-based model to strengthen the precise point positioning (PPP)/inertial navigation system (INS) tightly coupled model for land vehicles. However, the conventional NHC stochastic model cannot adapt to the sophisticated changing satellite observation conditions in the urban environment. Meanwhile, almost all literature focuses on the numerical performance of the NHC-aided PPP/INS tightly coupled system and lacks a comprehensive study on the effectiveness and applicability in the complex urban environment from the perspectives of theory and application. We dedicate to the theoretical analysis on the NHC contribution to the positioning solutions varying with diverse satellite observation conditions. A novel NHC stochastic model considering the changing observation condition is proposed to prevent the filtering error divergence caused by the biased NHC stochastic model. Moreover, the proposed model also suppresses the INS error accumulation during signal outages. Two road experiments with the Global Navigation Satellite System (GNSS) signal blockage simulations are conducted to verify the proposed model. The results indicate that the NHC-aided PPP/INS tightly coupled three-dimension positioning accuracy is improved by 33.3% in the partial blockage experiment. The multi-GNSS positioning accuracy is increased by 38.0% and 51.2% with the complete signal blockages in the experimental dataset 1 and dataset 2, respectively. Hence, the proposed NHC stochastic model can effectively avoid the filtering divergence caused by the biased NHC stochastic model and improve the filtering stability in the urban environment.