Precision-Aided Partial Ambiguity Resolution Scheme for Instantaneous RTK Positioning

The use of carrier phase data is the main driver for high-precision Global Navigation Satellite Systems (GNSS) positioning solutions, such as Real-Time Kinematic (RTK). However, observations are ambiguous by an unknown number cycles, and their in RTK relies on process mapping real-valued ambiguities to integer ones, so-called Integer Ambiguity Resolution (IAR). goal IAR enhance position solution virtue its correlation with estimated ambiguities. With deployment new GNSS constellations frequencies, a large available. While this generally positive, medium long baselines challenging due atmospheric residuals. In context, solving complete set ambiguities, Full (FAR), limiting may lead decreased availability precise positioning. Alternatively, Partial (PAR) relaxes condition estimating vector and, instead, finds subset them maximize availability. This article reviews state-of-the-art PAR schemes, addresses analytical performance estimator following generalization Cramér–Rao Bound (CRB) problem, introduces Precision-Driven (PD-PAR). latter constitutes scheme which employs formal precision (potentially fixed) selection criteria fix. Numerical simulations used showcase conventional FAR approaches, proposed PD-PAR against generalized CRB associated problems. Real-data experimental analysis baseline complements synthetic scenario. results demonstrate that (i) valid lower bound assess asymptotic behavior estimators, (ii) technique outperforms existing solutions non-recursive baselines.