Abstract-The measurement quality of Global Navigation Satellites Systems (GNSS) during marine operations will vary over time. Inherently, GNSS quality changes should be handled when GNSS is utilized as aid in inertial navigation systems. In this paper we present an observer for estimating position, velocity and attitude with time-varying gains for highperformance sensor fusion based on GNSS quality and other quality indicators. The origin of the error dynamics is proven to be uniformly semiglobal exponentially stable. The concept is illustrated by simulating a vessel operating in dynamic positioning with GNSS and inertial sensors.

Two of the major challenges with beyond visual line of sight (BVLOS) operations for unmanned aerial vehicles (UAVs) today are navigation and communication. This paper presents a solution that takes on both problems simultaneously, using a phased array radio system (PARS) both for communication and to aid a micro-electro-mechanical inertial navigation system (INS), estimating position, velocity and attitude. The solution is independent of global navigation satellite system (GNSS) for positioning and highly resistant to malicious sources, such as spoofing and jamming.

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In this article we suggest that a strapdown inertial navigation system based on MEMS inertial sensors is a useful addition to a vessel with dynamic positioning. We conduct full-scale experiments with MEMS inertial sensors on board a Dynamically Positioned (DP) offshore vessel operating off the Norwegian coast. The vessel operates in different scenarios, and the purpose is to showcase how low-cost MEMS sensors may complement or replace existing DP sensor systems. Employing nonlinear observers for estimating attitude, heave, velocity and position, we go through the benefits and disadvantages, and some caveats, for the sensors and methods used in this article. Two different MEMS units are evaluated, aided by gyrocompasses and position reference systems. We evaluate the attitude, heave and dead reckoning capabilities obtained with the presented estimators, in relation to relevant class notation, ultimately motivating the inclusion of new sensors and methods for dynamic positioning. The results related to attitude and heave are compared with data from well-proven industry standard vertical reference units while dead reckoning is evaluated with respect to the onboard position reference systems.