A Lightweight Motion Constraint Regulator for Enhanced GNSS/INS Tightly Coupled Integration in Urban Environments

Continuous, reliable, and real-time position information is essential for vehicle navigation. However, global navigation satellite system (GNSS) signals can be easily blocked or interfered with in urban environments, resulting in discontinuous and unreliable positioning. Nonholonomic constraint (NHC) is an effective and low-cost method for vehicle enhancement. However, accurate compensation for the mounting angle and lever arm and reasonable configuration of noise parameters are prerequisites for NHC to perform effectively. Unfortunately, existing studies often focus on only one aspect, neglecting the model's generalization ability and practicality (ease of implementation). To address this problem, we propose LVB-NHC, a lightweight motion constraint regulator based on variational Bayesian (VB), designed to enhance vehicle navigation in GNSS-constrained environments. The LVB-NHC uses the dead reckoning (DR) method to estimate the mounting angle and lever arm while employing the inverse gamma (IG) distribution to model the time-varying measurement noise covariance matrix (MNCM), thereby effectively addressing NHC inconsistency and uncertainty. Vehicle experiments demonstrate the algorithm's effectiveness and practicality.