Exploiting GNSS signal structure to enhance observability

There are a number of different error sources, such as multipath and thermal noise, which corrupt satellite navigation waveforms from their theoretical structure. However, even under ideal conditions the broadcast signals have some degree of deformation as a result of the practical individual hardware implementation. For the most demanding users of satellite navigation, such as aircraft navigation and landing systems, it is important to characterize the nominal signal structure in order to detect minimal variations resulting from hardware-based errors. Thus far such precorrelation Global Navigation Satellite System (GNSS) signal quality monitoring has been performed through high gain antennas, which allow for raising the GNSS spectrum above the thermal noise floor and observing the structure of the signal directly at the front end output. This paper describes a new approach to achieve such observability based on signal processing techniques, such as dithering and averaging, which leverage the repetitive nature of the GNSS signal. The paper presents how these techniques can drastically improve the signal-to-noise ratio (SNR) in postprocessing, allowing for the direct analysis of GNSS signals using traditional front end designs and conventional antennas. Results are predicted using the appropriate theory and validated using data collected from the Global Positioning System (GPS).     

Closed-loop distance-keeping for long-term satellite cluster flight

Cluster flight is a term used for describing multiple satellites that are being held within pre-defined minimum and maximum distances for long time intervals, possibly the entire mission. This technology is required for a myriad of space architectures and missions, including disaggregated space architectures. Whereas the literature is abundant with works on control laws for satellite formation flying, there are only a handful of works on control of cluster flight. The purpose of the current work is to develop a cluster flight control algorithm, which is able to keep the satellites of the cluster within pre-specified minimum and maximum distances, while utilizing small amounts of propellant. The newly developed algorithm relies on the natural inter-satellite distance dynamics. The algorithm incorporates realistic mission constraints, such as constant-magnitude thrust, and is implemented in feedback form, steering the mean elements to judiciously selected reference values. Simulations indicate that a few tens of grams of propellent are sufficient for operating a cluster flight mission in excess of 1 year, using low specific-impulse thrusters.     

The gauge-generalized Gyldén–Meshcherskii Problem

The Gyldén–Meshcherskii Problem (GMP) extends the classical two-body problem of Newton and Kepler by considering time-varying gravitating masses, an important extension of the two-body problem for modeling cometary motion and cosmological phenomena. In this paper, we consider the GMP in a specialized setup, the setup of gauge theory. We show that the variational equations, modeling the effect of the mass time variation on the orbital elements, can be derived by fixing a gauge of a particular form that is different from the Lagrange gauge. Thus, the orbital elements modeling the effect of a time-varying secondary mass are non-osculating. This implies that the trajectory of a celestial body whose mass is continuously changing cannot be approximated by a series of Keplerian orbits. Finally, we provide the first-order averaged equations written in terms of non-osculating elements.