With the rapid growth of operational satellites and debris in congested areas, such as Low Earth Orbit, moving in the traffic is becoming key also due to new regulations potentially coming into play. This paper presents a selection of current guidelines that can play a major role in small satellite mission design and presents the Delfi-Twin mission, conceived to demonstrate Space Traffic Management capabilities. The mission s made by two small satellites which will operate as a formation using differential drag as control strategy. On-board orbit determination will be employed to speed-up the availability of high-accuracy ephemeris and improve their dissemination to other operators. Miniaturized commercial receivers have been evaluated in an emulated orbital scenario to assess the performances of future on-board orbit determination system, providing some insights on existing problems related to commercial receivers not designed for operating in space.

The drag coefficient C_D of a satellite is an important input for predicting satellite orbits in low Earth orbit, but determining C_D is difficult due to limited knowledge of Gas-Surface Interactions (GSI), leading to orbit prediction errors and increased collision risk. We propose an experiment that leverages the concept of differential drag to gain more insight into GSI, as differential drag causes a varying frontal area and C_D while other conditions stay the same, allowing us to estimate GSI parameters using orbit determination. Both analytical and numerical methods to obtain C_D and their sensitivity to GSI parameters are discussed, and these methods are then used to determine the optimal maneuvers for the experiment. As a case study, simulations are shown of a planned experiment using the BRIK-II satellite of the Royal Netherlands Air Force. It is expected that this method can be used to obtain more knowledge on GSI modelling, as well as give satellite operators a method to estimate C_D of a satellite with less bias than conventional methods.

Uncertainty in atmospheric density models and drag coefficient modelling contributes to orbit prediction errors for satellites in Low Earth Orbit (LEO).
It is of interest to better characterise the Gas-Surface Interactions (GSI) to improve drag coefficient modelling, which is, however, hindered by a lack of dedicated in-orbit experiments. We propose a new experiment to estimate the energy accommodation coefficient of the Diffuse Reflection with Incomplete Accommodation (DRIA) GSI model. The experiment consists of two small satellites with Global Navigation Satellite Systems (GNSS) receivers and attitude determination systems to derive atmospheric density observations from the positioning data. The experiment has two key features. The first is the satellites' close along-track formation flying, such that they should observe the same atmospheric density with a slight delay due to their along-track separation. Second, the satellites have controllable panels to modify their drag coefficients' response to GSI substantially. Hence, the satellites' atmospheric density observations will agree only when the DRIA model's energy accommodation coefficient is selected correctly. We demonstrate by simulation that the energy accommodation coefficient can be estimated at least once daily with a precision of 5-10% for satellites with decimeter-accuracy GNSS positioning. Given that GNSS receivers and attitude determination systems are common for small satellites currently in LEO, we conclude that there are plenty of opportunities to utilise existing data for the proposed experiment. Valuable byproducts would be atmospheric density observations that are relatively free of systematic errors.

When the BepiColombo spacecraft arrives at Mercury in late 2025, it will be able to measure the orbit of the planet with unprecedented accuracy, allowing for more accurate measurements of the perihelion advance of the planet, as predicted by the Theory of General Relativity (GR). A similar effect is produced by the gravitational oblateness of the Sun through the zonal coefficient (Formula presented.). The gravitational field of the Sun has been hard to determine despite centuries of observations, causing great uncertainties in experiments on GR. Recent publications in heliophysics suggest that (Formula presented.) is not a constant, but a dynamic value that varies with solar magnetic activity. The aim of this paper is to analyse what the effect is of suggested higher-order effects of the solar gravitational field on experiments of the perihelion advance of Mercury as predicted by GR. The orbit of Mercury and observations of the MESSENGER and BepiColombo spacecraft are simulated, and parameters corresponding to gravitational theory, as well as the oblateness (Formula presented.) including a time-variable component are estimated using a least-squares approach. The result of the estimation is that the amplitude of a periodic component can be found with an uncertainty of (Formula presented.), equal to 0.017% the value of (Formula presented.). From analysis of published experiments that used MESSENGER tracking data, it can already be deduced that the amplitude of the periodic variation cannot be higher than 5% of the value of (Formula presented.). It is also found that if a periodic component exists with an amplitude greater than 0.04% the value of (Formula presented.) and it is not considered, it can lead to errors in the experiments of GR using BepiColombo data to the point that results falsely confirm or contradict the Theory of General Relativity.

The study of solar irradiance variability is of great importance in heliophysics, Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of features in the solar photosphere, chromosphere, and corona. Do coronal bright points contribute to the solar irradiance or its variability as input to the Earth atmosphere? We studied the variability of solar irradiance for a period of 10 years (May 2010 – June 2020) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA), and applied a linear model between the segmented features identified in the EUV images and the solar irradiance measured by LYRA. Based on EUV images from AIA, a spatial possibilistic clustering algorithm (SPoCA) is applied to identify coronal holes (CHs), and a morphological feature detection algorithm is applied to identify active regions (ARs), coronal bright points (BPs), and the quiet Sun (QS). The resulting segmentation maps were then applied on SWAP images, images of all AIA wavelengths, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/BPs/QS features were computed and compared with LYRA irradiance measurements as a proxy for ultraviolet irradiation incident to the Earth atmosphere. We modeled the relation between the solar disk features (ARs, CHs, BPs, and QS) applied to EUV images against the solar irradiance as measured by LYRA and the F10.7 radio flux. A straightforward linear model was used and corresponding coefficients computed using a Bayesian method, indicating a strong influence of active regions to the EUV irradiance as measured at Earth’s atmosphere. It is concluded that the long- and short-term fluctuations of the active regions drive the EUV signal as measured at Earth’s atmosphere. A significant contribution from the bright points to the LYRA irradiance could not be found.