Solar sailing is a propulsion method that uses solar radiation pressure (SRP) as main source of thrust. However, in close proximity of the Earth, SRP is not the only acceleration governing the sailcraft dynamics, as atmospheric drag and the Earth’s planetary radiation pressure (PRP) acceleration are also present. Because of their significant magnitudes relative to the SRP acceleration, these accelerations could potentially be exploited by the sail to maneuver more effectively around the Earth. Nevertheless, the majority of research conducted on Earth-bound solar sailing to date either neglects these accelerations or treats them as uncontrollable sources of perturbation. This hinders accurate prediction of the sailcraft’s maneuvering capabilities and, accordingly, the accurate design of future solar-sail missions. In view of this, this paper presents a trajectory optimization method developed in conjunction with a high-fidelity model of the near-Earth dynamical environment, used to comprehensively characterize the maneuvering capabilities of solar sails in proximity of the Earth. The optimization algorithm is designed to change any orbital element in a locally optimal manner, while accounting for and optimally controlling the SRP, PRP, and aerodynamic accelerations. Following its introduction, the algorithm is exploited to characterize the maneuverability of Earth-bound solar sails, taking NASA’s recently-launched ACS3 solar-sail mission as a baseline. Specifically, different sensitivity analyses are conducted to determine ACS3’s orbit-raising and inclination-changing capabilities for a large set of orbits, times of the year, solar activities, and sailcraft characteristics. The results of this study not only enhance the understanding of ACS3’s performance but also provide valuable insights for the mission design of future Earth-bound solar-sail missions for a variety of mission applications, ranging from active-debris removal and collision avoidance, to orbit maintenance and in-orbit servicing.

The ESA GOCE satellite carried a gravity gradiometer consisting of three pairs of accelerometers on mutually orthogonal axes. For each accelerometer, bias and scale factors have been re-estimated by a dynamic precise orbit determination (POD) using improved gravity field modeling and standards. The kinematic orbit solution included in GPS-based Precise Science Orbit (PSO) product served as the baseline observables for 1210 daily arcs, covering the period from 1 November 2009 to 20 October 2013. Implementing improved force models almost completely resolved the deviations of the Y-axis scale factor obtained in earlier work (Visser and Ijssel 2016). A novel aspect is the verification by comparison with dynamic POD solutions based on SLR observations using 51 two-day orbital arcs. A high level of consistency was obtained between the kinematic PSO- and SLR-based accelerometer calibration parameters, e.g. within 0.01 nm/s2 for the X-axis pointing predominantly in the flight direction in terms of bias. One set of accelerometer scale factors was estimated for the entire mission. These were found to be consistent to within 0.005 for all accelerometer axes. The three-dimensional consistency between the dynamic orbits and the PSO reduced-dynamic orbit solutions has a mean Root-Mean-Square (RMS) of 4.5 and 10 cm, respectively, for the PSO reduced-dynamic and SLR-based dynamic orbit solutions. In addition, the one-dimensional RMS-of-fit of the PSO kinematic orbit solution improved significantly from 6.9 in Visser and Ijssel (2016) to 2.6 cm.

Significant research has addressed solar-sail transfers in heliocentric settings, whereas planet-centered transfers have received comparatively little attention. However, most solar-sail missions flown to date have operated in Earth-centered orbits and are likely to continue to do so, highlighting the importance of planet-centered sailing in the future of this new and promising technology. This work fully characterizes the co-planar multi-revolution circular-to-circular (MC2C) transfers, which enable motion between co-planar circular orbits and are therefore regarded as one of the “simplest” possible planet-centered solar-sail transfers. Using an indirect optimization approach, the performance of the MC2C transfers (i.e., achieved radius change in a fixed transfer time) is computed for various initial sun-orbit geometries. As a result, the best and worst transfer geometries (which depend on the illumination conditions of the orbital plane) are identified, enabling the construction of the performance envelopes that relate radius change to transfer time. These envelopes provide a simple graphical tool to obtain such metrics without having to optimize a single trajectory, greatly enhancing the workflow during early mission design. Through dimensional analysis, the envelopes are generalized to any sail design and any planet in the solar system, broadening their applicability. Finally, the explanation of the physical mechanisms behind the best and worst geometries is provided through new concepts that are unique to solar sailing, like the “growth vector”. This explanation lies the foundation for the study of future, more complex planet-centered solar-sail transfers.

Valuable insights into the thermospheric mass density and horizontal winds can be obtained from satellites equipped with accelerometers. To derive these quantities, radiation pressure must be accurately modeled and removed from the calibrated accelerometer measurements. However, the documented surface reflection and absorption coefficients, as well as the satellite’s thermal properties, are often inaccurate or, in some cases, even absent. This study presents a method for optimizing these parameters jointly with the accelerometer scale factors. Focusing on GRACE data from 2009, a case where radiation pressure was dominant over aerodynamic force, enabled us to refine the radiation pressure model without detrimental effects from errors in aerodynamic force modeling. We evaluated three variants of estimating the scale factor: estimating no accelerometer scale factors, only the y-axis scale factor, or both the y- and z-axis scale factors. We use the difference between the measured and modeled accelerations (the residual) as our target functional. Estimating both scale factors yielded the lowest residual for both GRACE satellites, even though the radiation pressure model was tuned using GRACE-A data only. After the optimization, we observed a systematic feature in the cross-track residuals within the geographical domain, which strongly correlates with the magnetic field vector experienced by the spacecraft. While its cause remains unknown, we introduced an empirical correction that effectively removed the feature and significantly increased consistency between GRACE-A and GRACE-B. Overall, we were able to reduce the RMS of the residuals by more than 13% in the cross-track direction and 32% in the radial direction, indicating a significant increase in modeling accuracy. The presented method provides a generalizable approach that can also be applied to future satellite missions with accelerometers.

NASA's ACS3 mission aims to be the first Earth-bound solar sail to execute calibration steering laws for in-orbit estimation of solar-sail acceleration parameters. To maximise the mission's scientific return, this study identifies the physical effects to include in the dynamical model, the solar-sail acceleration parameters observable from flight data, and the uncertainties to consider during the orbit determination process. The sensitivity of the solar-sail dynamics to perturbations, model uncertainties, and sail-attitude errors is investigated by 1) comparing a reference orbit with modified orbits, each altered in a single dynamical aspect, and 2) evaluating the accuracy of modified models in reconstructing the reference orbit through iterative initial state adjustments. For the one-sigma 10-meter observation noise level of the ACS3 mission and a seven-day arc, results indicate that higher-order lunar perturbations, planetary third-body effects, and relativistic corrections can be omitted from the dynamical model. Additionally, the geopotential expansion may be limited to degree and order 32. In contrast, the dynamics should include the effects of solid Earth tides, account for the instantaneous Sun-sailcraft distance in the solar radiation pressure model, and assume imperfect reflection from the sail surface in the solar and planetary radiation pressure models. Furthermore, the analysis reveals varying levels of observability for the sail optical coefficients, with frontside reflectivity and specularity showing the strongest influence on the solar-sail dynamics. Finally, systematic attitude errors and uncertainties in atmospheric density and accommodation coefficients are the most challenging factors to absorb through initial state adjustment, potentially complicating the estimation of solar-sail acceleration parameters.

The Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite, which operated at an altitude of ∼250km, provided neutral thermosphere mass density and crosswind observations in the dawn-dusk sectors throughout most of its operational lifetime (2009–2013). As a result of its Sun-synchronous orbit, GOCE’s large solar panels remained at a near-perpendicular angle to the incoming solar radiation, leading to a significant radiation pressure acceleration. In this research, we focused on revisiting and reprocessing GOCE thermosphere mass density and crosswind data. We selected the coefficients describing the thermo-optical surface properties and employed a high-fidelity satellite geometry in a ray-racing simulation. Additionally, we distinguished between the solar flux in the visible and infrared bands and introduced a model for the satellite’s thermal emission. The availability of the in situ thermistor measurements allowed for the validation of the thermal model. Moreover, we replaced the Level-1b ion thruster data with raw telemetry, filling multiple data gaps. We analysed how incremental improvements in the radiation pressure modelling affected the observed crosswind speed. By replacing the panel model with the high-fidelity satellite geometry, the crosswind speed decreased up to 5 ms⁻¹. The biggest difference reduction of 40ms⁻¹resulted from introducing the thermal model. Splitting the solar flux further decreases the observed crosswind speed by up to 8ms⁻¹. The reduction in crosswind speed was most prominent during the first years of the mission when the solar activity was low. We compared the newly processed GOCE zonal wind data with respect to the most recent previous release. We observed a median absolute deviation decrease of 10 ms⁻¹around the south magnetic pole in the dawn sector. The yearly consistency of low-latitude zonal winds did not change significantly. The main obstacle in quantifying the improvement compared to the previous crosswind dataset stemmed from the fact that the previous and new datasets were generated with different crosswind estimation algorithms. The difference in thermosphere density compared to previously published datasets is minor since the effect of radiation pressure is most prominent in the cross-track direction. Finally, we verified the assumption about the energy accommodation coefficient of 0.82 and concluded that it remains valid after implementing the radiation pressure modelling improvements.

Uncertainties in radiation pressure modelling play a significant role in the thermospheric density and crosswind observations derived from the GRACE-FO accelerometer, especially during low solar activity. Under such conditions, the radiation pressure acceleration matches the magnitude of the aerodynamic acceleration along the track and exceeds it in the cross-track direction. The GRACE-FO mission has been operating for several years at such high altitudes during both low and rising solar activity, providing a perfect opportunity to study the effects of radiation pressure. This research uses ray tracing based on a high-fidelity satellite geometry model to calculate the radiation pressure acceleration. We numerically fine-tuned the coefficients describing the thermo-optical surface properties to obtain more accurate radiation pressure accelerations than those specified in the GRACE-FO mission manual. We also used in situ temperature measurements from thermistors on the solar arrays to model the satellite's thermal emission. These temperature measurements allowed a realistic setup of the thermal model, extended by the parameter describing the efficiency of the solar cells, and reproduced the acceleration of the thermal emission with an accuracy of RMS 0.148 nms⁻². The combination of the updated thermal model and the fine-tuning of the surface coefficients improved the accuracy of the crosswind acceleration to an RMS of 0.55 nms⁻², compared to an RMS of 4.22 nms⁻² when using panel models and instantaneous thermal radiation. We compared the observed crosswind with two models: HWM14 and TIE-GCM. While both models capture most of the salient features of the observed crosswind, HWM14 shows particularly good agreement at high latitudes. Compared to the previously employed radiation pressure model, the crosswind observations have been improved in low and mid-latitudes, especially during periods of higher solar activity. Since the effect of radiation pressure is most significant in the crosswind direction, the effect on density was small compared to previously published datasets.

This study investigates the influence of ocean currents on wave modeling and satellite observations using in situ wave measurements from the One Ocean Expedition 2021–2023. In January 2023, six OpenMetBuoy drifters were deployed in the Agulhas Current region. Their high immersion ratio minimized wind effects, allowing them to follow the current and return to the Indian Ocean by the Agulhas retroflection, collecting data for about 2 months. Comparing surface current velocities from both the Mercator model and Globcurrent product with drifter data reveals underestimation for velocities over (Formula presented.) with Mercator showing greater variability. Significant wave height and Stokes drift parameters from MFWAM and ERA5 were also evaluated against drifters. Both models tend to overestimate Stokes drift more noticeable in ERA5, indicating sensitivity to wind seas. For significant wave height, both models agree well with drifter measurements with correlations of 0.90 for MFWAM and 0.83 for ERA5. However, ERA5's lack of surface current data combined with its coarse resolution (0.5 (Formula presented.)) lead to underestimation of wave heights exceeding 2.5 m. MFWAM products including and excluding currents exhibit root mean square errors of 0.39 and 0.45 m, respectively, when compared to drifter measurements. This confirms that neglecting currents introduces additional errors particularly in areas with sharp current gradients. Analyzing MFWAM wave spectra, including and excluding currents, reveals wave energy transfer attributed to wave-current interactions. The spatial extent of these interactions is captured by satellite altimeters, revealing wave modulations with considerable wave height variations when waves cross eddies and the current core.

In the coming decade, JUICE and Europa Clipper radio-science will yield the most accurate estimation to date of the Galilean moons’ physical parameters and ephemerides. JUICE's PRIDE (Planetary Radio Interferometry and Doppler Experiment) will help achieve such a solution by providing VLBI (Very Long Baseline Interferometry) observations of the spacecraft's lateral position, complementing nominal radio-science measurements. In this paper, we quantify how PRIDE VLBI can contribute to the moons’ ephemerides determination, in terms of attainable solution improvement and validation opportunities. To this end, we simulated VLBI data for JUICE, but also investigated the possibility to perform simultaneous tracking of JUICE and Europa Clipper, thus ultimately generating both single- and dual-spacecraft VLBI. We considered various tracking and data quality scenarios for both VLBI types, and compared the formal uncertainties provided by covariance analyses with and without VLBI. These analyses were performed for both global and local (i.e. per-flyby) estimations of the moons’ states, as eventually achieving a global solution first requires proceeding arc-per-arc. We showed that both single- and multi-spacecraft VLBI measurements only bring limited improvement to the global state estimation, but significantly contribute to the moons’ normal points (i.e. local states at flyby times), most notably in the out-of-plane direction. Additionally, we designed a validation plan exploiting PRIDE VLBI to progressively validate the classical radio-science solution, whose robustness and statistical realism is sensitive to modelling inconsistencies. By improving the local state estimations and offering various validation opportunities, PRIDE will be invaluable in overcoming possible dynamical challenges. It can therefore play a key role in reconstructing a global solution for the Galilean moons’ dynamics with the uncertainty levels promised by JUICE-Europa Clipper analyses. This, in turn, is critical to the accurate characterisation of tidal dissipation in the Jovian system, holding the key to the long-term evolution of the Galilean moons.

Autonomous Line-of-Sight navigation represents an appealing technique that can be exploited by deep-space spacecraft, particularly miniaturized, to estimate the state during cruising. It is based on the observation of visible bodies' directions, processed onboard to estimate the spacecraft' 6D heliocentric state. Its applicability has been preliminarily investigated by feeding the navigation filter with simplified measurements, simulated by adding a certain noise on the actual direction, based on star-tracker characteristics. However, while this approach is convenient and appropriate for a preliminary study, it is not sufficient to dive into the characteristics and performance of the method, and later on to definitely prove its applicability to real missions. This is because the measurement error cannot be considered relying exclusively on the star tracker's characteristics, as the observation scenario (e.g. planet apparent size, illumination condition, stars background) does play an important role in the measurement error. For this reason, in this work, we include image processing in the simulation loop. First, we define how to simulate realistic and reliable synthetic space images as a function of hardware characteristics and observation scenarios; then we use the generated images within the simulation to compute the measurements. Thanks to this approach, it is also possible to further improve the navigation filter design. In fact, we developed an Adaptive Extended Kalman Filter to cope with variable measurement errors and dynamics conditions. This filter allows the automatic tuning of both the process noise covariance and the measurement noise matrices as a function of the scenario. With this work, we add two important pieces to the road map for fully autonomous deep-space spacecraft: performance evaluation refinement including image-processing, and design of AEKF for the technique.