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

Inland shipping is an important pillar of the European transport system, however due to dense traffic, reduced visibility and increasing ship dimensions it is very challenging. About 20 to 30 collisions per year, mainly caused by carelessness, lead to damages on waterway infrastructures like bridges, damages on the vessel or even injured people. This fact demonstrates the necessity of driving assistance functions for inland vessels. This contribution will give an overview about the concluded project LAESSI which includes the require-ments for accuracy, integrity and time to alert for the different assistance functions as well as the de-scription of the complete overall system setup like shore-based and board equipment. A main topic in this project was the first realization of the new communication concept based on VHF Data Exchange System (VDES) the next generation of the AIS communication which will also present here. A challenge in this communication concept was the limited data capacity for transmitting all necessary phase and code corrections for every observation in every epoch.