Understanding of what is achievable with solar-sail technology around planetary bodies is in its infancy. The seemingly simple problem of transferring from one circular orbit to another circular orbit with a solar sail around a planet is yet to be fully characterized. This work aims to start filling that gap by analyzing the coplanar patched multirevolution circular-to-circular (PMC2C) transfer. The PMC2C transfer is a continuous sequence of single-revolution circular-to-circular (SC2C) transfers, where each SC2C transfer is optimized for the achieved radius change in one orbital revolution. Then, the radius change and transfer time of a PMC2C transfer is obtained as the aggregation of the individual SC2C increments. To generalize to all initial geometries, hundreds of PMC2C transfers must be computed, which is not feasible in practice. To bypass this problem, the so-called patched method is proposed. The patched method uses a semianalytical approach to estimate the radius change and the transfer time of the PMC2C transfers, effectively removing the need for numerical optimization. Dimensionless in nature, the patched method can be used for any sail design around any planet orbiting a star. With this tool, early mission design is greatly simplified; hundreds of trajectories can be analyzed in a matter of minutes. In addition, the generalized formulation reveals the best and worst orbital geometries and initial epochs to start a PMC2C transfer, improving general knowledge of how to “sail” around planets.

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.

The growing number of space objects in low-Earth orbit necessitates accurate orbit predictions to decrease the likelihood of operational disruptions. The challenges in accurately capturing how gas particles interact with the objects’ surfaces result in uncertainties in their aerodynamic coefficients, directly affecting the accuracy of orbital perturbation models. Currently, gas–solid boundary interactions are accounted for by empirical models like those proposed by Sentman and Cercignani-Lampis-Lord. These models have one or two adjustable parameters, typically tuned based on orbital tracking and acceleration data. However, these models are inadequate in accurately representing crucial processes at the gas–solid interface such as multiple reflections, shadowing, and backscattering resulting from the roughness of real surfaces. We propose a new, physics-based gas-surface interaction model that leverages electromagnetic wave theory to incorporate macroscopic effects on the gas particle scattering distribution resulting from surface roughness. Besides better describing the physics of gas-surface interaction, this model’s parameters can be determined by combining ground measurements to characterise the surface roughness and molecular dynamics simulations to specify the atomic-scale interaction. The model is verified for the entire parameter range using a test-particle Monte Carlo approach on a simulated rough surface. In addition, we successfully replicate several experimental results available in literature on the scattering of Argon and Helium on smooth and rough Kapton and Aluminium surfaces. We conclude by demonstrating the model’s effect on the aerodynamic coefficients for simple shapes and comparing these results with those produced with the Sentman and Cercignani-Lampis-Lord models, thereby demonstrating that previously observed inconsistencies between these models and tracking data of spherical satellites can be explained by surface roughness.

We present the first extensive analysis of K/Ka-band ranging post-fit residuals of an official Level-2 product, characterized as Line-of-Sight Gravity Differences (LGD), which exhibit and showcase interesting sub-monthly geophysical signals. These residuals, provided by Center for Space Research, were derived from the difference between spherical harmonic coefficient least-squares fits and reduced Level-1B range-rate observations. We classified the geophysical signals into four distinct categories: oceanic, meteorological, hydrological, and solid Earth, focusing primarily on the first three categories in this study. In our examination of oceanic processes, we identified notable mass anomalies in the Argentine basin, specifically within the Zapiola Rise, where persistent remnants of the rotating dipole-like modes are evident in the LGD post-fit residuals. Our analysis extended to the Gulf of Carpentaria and Australia during the 2013 Oswald cyclone, revealing significant LGD residual anomalies that correlate with cyclone tracking and precipitation data. Additionally, we investigated the monsoon seasons in Bangladesh, particularly from June–September 2007, where we observed peaks in sub-monthly variability. These findings were further validated by demonstrating high spatial and temporal correlations between gridded LGD residuals and ITSG-Grace2018 daily solutions. These identified anomalies are associated with significant mass change phenomena, underscoring the critical importance of these geophysical signals for future high-resolution studies of mass transport.

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.

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.

NASA’s ACS3 mission will be the first Earth-bound solar-sail mission to fly so-called calibration steering laws. These steering laws are designed to expose the sailcraft to a variety of dynamical conditions to isolate the effects of different parameters on the dynamics, thereby facilitating the estimation of these parameters. This paper presents the set of candidate calibration steering laws of ACS3, highlighting their operational challenges and impact on the estimation of the sail’s reflectivity and specularity. The results show that, for a conservative GPS position accuracy of 10 m, accurate estimation of the reflectivity and specularity with uncertainties in the order of 10−4 − 10−3 can be achieved by flying any of the proposed calibration laws. However, ACS3’s calibration steering laws were also found to introduce operational challenges that may hinder their implementation for extended periods of time. In particular, the decreased power generation capability of solar arrays was found to be the most severe operational challenge for two out of the five ACS3’s calibration laws analysed.

This study presents the first azimuth cutoff analysis in Synthetic Aperture Radar (SAR) altimetry, aiming to assess its applicability in characterizing sea-state dynamics. In SAR imaging, the azimuth cutoff serves as a proxy for the shortest waves, in terms of wavelength, that can be detected by the satellite under certain wind and wave conditions. The magnitude of this parameter is closely related to the wave orbital velocity variance, a key parameter for characterizing wind-wave systems. We exploit wave modulations exhibited in the tail of fully-focused SAR waveforms and extract the azimuth cutoff from the radar signal through the analysis of its along-track autocorrelation function. We showcase the capability of Sentinel-6A in deriving these two parameters based on analyses in the spatial and wavenumber domains, accompanied by a discussion of the limitations. We use Level-1A high-resolution Sentinel-6A data from one repeat cycle (10 days) globally to verify our findings against wave modeled data. In the spatial domain analysis, the estimation of azimuth cutoff involves fitting a Gaussian function to the along-track autocorrelation function. Results reveal pronounced dependencies on wind speed and significant wave height, factors primarily determining the magnitude of the velocity variance. In extreme sea states, the parameters are underestimated by the altimeter, while in relatively calm sea states and in the presence of swells, a substantial overestimation trend is observed. We introduce an alternative approach to extract the azimuth cutoff by identifying the fall-off wavenumber in the wavenumber domain. Results indicate effective mitigation of swell-induced errors, with some additional sensitivity to extreme sea states compared to the spatial domain approach.

Solar sailing is a propulsion method that takes advantage of solar radiation pressure to generate thrust. Although most of near-future solar-sail missions will fly in low Earth orbit, where planetary radiation pressure can be as large as 20% of solar radiation pressure, studies on the accelerations produced by the Earth’s albedo and blackbody radiation have only been conducted to a very limited first-order extent. This paper therefore provides a novel, detailed analytical model for these perturbing accelerations, valid for perfectly reflecting solar sails. The full derivation of the model is described, and a thorough analysis of the blackbody and albedo radiation pressure accelerations is conducted for different orbital conditions. Then, to determine the model’s accuracy, a comparison with the state of the art (the finite-disk radiation source model and a high-fidelity numerical model) is provided. Ultimately, different analyses to quantify the effect of planetary radiation pressure acceleration on the solar-sail maneuvering capabilities are presented, using NASA’s upcoming ACS3 mission as reference scenario. The results highlight the nonnegligible effect of uncontrolled planetary radiation pressure acceleration, which can reduce the sailcraft’s achievable altitude and inclination gains to 76 and 80%, respectively, of the gains obtained when planetary radiation pressure is not accounted for.

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.

Thermosphere mass density and crosswind can be derived from accelerometer and GNSS tracking data. However, present datasets are often provided without comprehensive uncertainty specifications. We present a newly developed method that propagates measurement noise and errors in the satellite specification, thermosphere models, and radiation flux data to density observations to quantify their uncertainty. We focus specifically on density observations derived only from GNSS tracking data, which are limited in resolution along the orbit due to unavoidable smoothing. While the method can be applied to simulated and real data, making it useful for existing datasets and mission design, we demonstrated it using data from the GRACE B satellite. First, we compare the aerodynamic acceleration derived separately from the accelerometer and GNSS tracking data, highlighting the role of two significant noise sources: noise due to the differentiation of the positions and noise from the evaluation of the gravity vector at a noisy position. Averaging substantially reduces the noise in the aerodynamic acceleration as long as the differentiation noise dominates, which is the case at frequencies higher than the orbital frequency. Below, gravity vector evaluation noise becomes the dominating noise source, and consequently, averaging over longer periods leads to only marginal uncertainty reduction. Further, we investigate the uncertainty in the radiation pressure acceleration and demonstrate that averaging over one orbit substantially reduces the uncertainty in the along-track radiation pressure acceleration. We show that the uncertainty of density observations derived from the accelerometer data is about 4% of the density for data from 2003 when the GRACE B satellite was at 490km altitude during high solar activity. In 2008, solar activity was very low, and the altitude was still 476km, resulting in an uncertainty of 5%–20% because GNSS tracking noise and radiation pressure modeling errors play a much larger role as the aerodynamic acceleration becomes smaller. In the case of density observations derived only from GNSS tracking data, the uncertainty is about 5% in 2003 and 20%–50% in 2008 when averaging over one-third orbit. In 2008, GNSS tracking noise explains nearly all uncertainty in the density observation. Averaging over one orbit reduces the uncertainty to 4% and 5% in 2003 and 2008, respectively.

Solar sailing is a propulsion method that uses solar radiation pressure (SRP) as main source of thrust and is therefore particularly suited for heliocentric flight regimes. However, the vast majority of sailcraft launched to date have flown around Earth, as will those scheduled for launch in the near future. Around the Earth, the dynamics of a solar sail are affected by the presence of eclipses and additional sources of acceleration apart from SRP, in particular, atmospheric drag and the Earth’s planetary radiation pressure (PRP). These accelerations can reach magnitudes in the order of (or even larger than) the SRP acceleration and, therefore, they can potentially be exploited to manoeuvre more effectively around the Earth. Nevertheless, the majority of research conducted on Earth-bound solar sailing either neglects these accelerations or treats them as uncontrollable sources of perturbation. In light of this, this paper presents a high-fidelity trajectory optimisation method which is then used to thoroughly characterise the manoeuvring capabilities of solar sails in the near-Earth environment. The optimisation algorithm is designed to change any orbital element in a locally optimal manner while accounting for the SRP, PRP, aerodynamic, and gravitational accelerations. To tune the optimiser, a first-order analysis of the accelerations achievable by sailcraft in proximity of the Earth is discussed. Then, the optimisation algorithm is exploited to fully characterise the manoeuvring capabilities of Earth-bound solar sails, taking NASA’s recently-launched ACS3 solar-sail mission as a baseline. Specifically, different parametric analyses are conducted to determine ACS3’s orbit-raising and inclination-changing capabilities for a large set of orbits, 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, such as active-debris removal and in-orbit servicing.

The problem of how to solar sail around planets remains nearly unexplored. Most of the existing body of knowledge focuses on scape trajectories or locally optimal controls, not providing much insight into the inherent physical characteristics of the transfer problem. In this work, we present the first comprehensive study of solar-sail transfers around planetary bodies by analysing the simplest conceivable transfer, the planar Circular-to-Circular (C2C) transfer. The C2C transfer spans for only one orbital revolution, constituting the building block of more complex multi-revolution trajectories. By patching together a series of C2C transfers, a feasible initial guess for trajectory optimisation algorithms can be generated. The optimised control law maximises the orbital radius within the C2C transfer. The radius change is used as performance metric. The results suggest that the domain of the control variables can be substantially reduced, effectively enhancing convergence of the optimal control solver, and significantly reducing computational time. Furthermore, a dimensional analysis shows that the C2C performance only depends on one parameter: the ratio of the sail’s characteristic acceleration over the local gravitational acceleration. The scaled nature of the results allows to easily compute the C2C performance for a wide range of mission scenarios around any planetary body, providing a new tool for early mission design.

Solar sailing is a propellantless propulsion method that exploits solar radiation pressure to generate thrust. In recent years, several solar sails have been launched into Earth-bound orbit to demonstrate this technology’s potential. Because planetary radiation pressure can reach magnitudes comparable to that of solar radiation pressure in proximity of the Earth, it cannot automatically be neglected in near-Earth solar-sail mission design studies. Nevertheless, its effect on the solar-sail dynamics has been investigated only to a very limited, first-order extent, and every study considered an “ideal” – i.e., perfectly reflecting – sail model. Although employing the ideal sail model proves useful for preliminary orbital analyses, its limited fidelity prevents more in-depth research into the near-Earth solar-sail dynamics and trajectory optimization. In light of this, this paper provides a new planetary radiation pressure acceleration model for optical solar sails. This model forms an extension of the “spherical” planetary radiation pressure acceleration model for ideal solar sails devised by Carzana et al. in Reference [1]. In the current paper, the underlying assumptions and full derivation of the newly devised optical model are presented. Subsequently, the accuracy of the optical model is analyzed through a comparison with the ideal model, using NASA’s upcoming ACS3 mission as reference scenario.

This manuscript aims to present and evaluate the applicability of combining optical line-of-sight (LoS) navigation with crosslink radiometric navigation for deep-space cruising distributed space systems. To do so, a set of four distributed space systems architectures is presented, and for each of those, the applicability of the combination is evaluated, comparing it to the baseline solutions, which are based on only optical navigation. The comparison is done by studying the performance in a circular heliocentric orbit in seven different time intervals (ranging from 2024 to 2032) and exploiting the observation of all the pairs of planets from Mercury to Saturn. The distance between spacecraft is kept around 200 km. Later, a NEA mission test case is generated in order to explore the applicability to a more realistic case. This analysis shows that the technique can also cope with a variable inter-satellite distance, and the best performance is obtained when the spacecraft get closer to each other.

ESA’s Earth explorer mission CryoSat-2 has an ice-monitoring objective, but it has proven to also be a valuable source of observations for measuring impacts of climate change over oceans. In this paper, we report on our long-term ocean data analysis and validation and give our final words on CryoSat-2’s Geophysical Ocean Products (GOP) Baseline-C. The validation is based on a cross comparison with concurrent altimetry and with in situ tide gauges. The highlights of our findings include GOP Baseline-C showing issues with the ionosphere and pole tide correction. The latter gives rise to an east–west pattern in range bias. Between Synthetic Aperture Radar (SAR) and Low-Resolution Mode (LRM), a 1.4 cm jump in range bias is explained by a 0.5 cm jump in sea state bias, which relates to a significant wave height SAR-LRM jump of 10.5 cm. The remaining 0.9 cm is due to a range bias between ascending and descending passes, exhibiting a clear north–south pattern and ascribed to a timing bias of +0.367 ms, affecting both time-tag and elevation. The overall range bias of GOP Baseline-C is established at −2.9 cm, referenced to all calibrated concurrent altimeter missions. The bias drift does not exceed 0.2 mm/yr, leading to the conclusion that GOP Baseline-C is substantially stable and measures up to the altimeter reference missions. This is confirmed by tide gauge comparison with a selected set of 309 PSMSL tide gauges over 2010–2022: we determined a correlation of R = 0.82, a mean standard deviation of (Formula presented.) cm (common reference and GIA corrected), and a drift of 0.17 mm/yr. In conclusion, the quality, continuity, and reference of GOP Baseline-C is exceptionally good and stable over time, and no proof of any deterioration or platform aging has been found. Any improvements for the next CryoSat-2 Baselines could come from sea state bias optimization, ionosphere and pole tide correction improvement, and applying a calibrated value for any timing biases.

Planetary Radio Interferometry and Doppler Experiment (PRIDE) is a multi-purpose experimental technique aimed at enhancing the science return of planetary missions. The technique exploits the science payload and spacecraft service systems without requiring a dedicated onboard instrumentation or imposing on the existing instrumentation any special for PRIDE requirements. PRIDE is based on the near-field phase-referencing Very Long Baseline Interferometry (VLBI) and evaluation of the Doppler shift of the radio signal transmitted by spacecraft by observing it with multiple Earth-based radio telescopes. The methodology of PRIDE has been developed initially at the Joint Institute for VLBI ERIC (JIVE) for tracking the ESA’s Huygens Probe during its descent in the atmosphere of Titan in 2005. From that point on, the technique has been demonstrated for various planetary and other space science missions. The estimates of lateral position of the target spacecraft are done using the phase-referencing VLBI technique. Together with radial Doppler estimates, these observables can be used for a variety of applications, including improving the knowledge of the spacecraft state vector. The PRIDE measurements can be applied to a broad scope of research fields including studies of atmospheres through the use of radio occultations, the improvement of planetary and satellite ephemerides, as well as gravity field parameters and other geodetic properties of interest, and estimations of interplanetary plasma properties. This paper presents the implementation of PRIDE as a component of the ESA’s Jupiter Icy Moons Explorer (JUICE) mission.

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.