Momentum Exchange with Electrodynamic Reboost (MXER) tethers transfer captured payloads to higher orbits using a long, rotating tether. This transfer occurs through a momentum exchange from the tether to the payload, after which the tether's orbital energy is restored via electrodynamic thrusting. MXER tethers offer a sustainable, reusable, and near-propellantless alternative to rockets for orbital and interplanetary transfer of payloads. However, the short rendezvous window for tether payload capture, typically lasting mere seconds, presents a significant challenge to the use of these tether systems. This research investigates the control of MXER tether dynamics, aiming to improve payload capture success by extending the rendezvous window. This work compares three actuator configurations (a baseline tip-reeling system, a climbing actuator mass, and a reeling actuator mass) previously studied for librating tethers, adapting them for a rotating MXER system based on the Cislunar Tether Transport System design. A 2D rigid-body model is used to simulate the system dynamics. Initially, a conventional iterative Linear Quadratic Regulator (iLQR) establishes a baseline for control performance. Subsequently, the model-free Soft Actor-Critic (SAC) Deep Reinforcement Learning (RL) algorithm is implemented and trained. Both control methods were tested with and without dynamic system constraints. The performance of each configuration is evaluated based on rendezvous window extension and constraint satisfaction. In the unconstrained case, the reeler configuration is shown to be the most effective, extending the rendezvous window to 1.8 seconds from the 0.6 seconds for the uncontrolled case. The SAC RL algorithm matches the performance of the tuned iLQR controller, but produces a less smooth control policy with sporadic actuator use. The constrained control proved more challenging, with neither the augmented-Lagrangian iLQR nor the SAC-based controller managing to extend the rendezvous window; the former was overly conservative, while the latter failed to satisfy operational constraints.

Optimal solutions to spacecraft routing problems are essential for space logistics activity such as Active Debris Removal (ADR), which addresses the growing threat of space debris. This research investigates the effectiveness of Neural Combinatorial Optimization (NCO) methods for the autonomous planning of low-thrust, multi-target ADR missions, an instance of the Space Traveling Salesman Problem (STSP). An autoregressive, attention-based routing policy was trained to solve 10-transfer ADR routing problems using REINFORCE, Advantage Actor-Critic, and Proximal Policy Optimization. A hyperparameter sensitivity analysis identified embedding dimension and the number of encoder layers as the critical factors influencing model performance, while an ablation study found the attention-based encoder to be the most critical architectural component of the policy. The trained policy was evaluated on 10-, 30-, and 50-transfer scenarios based on the Iridium 33 debris cloud, comparing its performance to a baseline provided by a novel ADR STSP routing heuristic (Dynamic RAAN Walk, DRW) and near-optimal benchmarks obtained via Heuristic Combinatorial Optimization (HCO). In missions with 10 transfers, the NCO policy achieved a mean optimality gap of 32%, outperforming DRW. However, performance degraded significantly in scenarios with 30 and 50 transfers, suggesting limited generalization to larger problems. A hyperparameter search further revealed that the performance of the NCO model considered in this work improves asymptotically with its size. Exposure to greater numbers of training scenarios did not yield significant performance gains. This work demonstrates that NCO methods can be effective for the autonomous planning of ADR missions with a limited number of targets, but face scalability and generalization challenges in more complex scenarios.

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.

The provinces of Bangkok, Samut Prakan, Samut Sakhon, and Nakhon Pathom in Thailand are experiencing subsidence caused by land subsidence, tectonic activity, and sea-level rise. INSAR result from 2015-2022 show that Bangkok and nearby provinces subsided up to 3 cm/yr in the past 20 years. GNSS results show absolute subsidence rates (below 20 m) up to 5 mm/yr in the past 25 years. According to satellite altimetry data, Bangkok is currently experiencing a sea-level rise of up to 5 mm per year in the Gulf of Thailand. Ground water pumping also play an important role on land subsidence.

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.

In the Arctic Ocean, obtaining water levels from satellite altimetry is hampered by the presence of sea ice. Hence, water level retrieval requires accurate detection of fractures in the sea ice (leads). This paper describes a thorough assessment of various surface type classification methods, including a thresholding method, nine supervised-, and two unsupervised machine learning methods, applied to Sentinel-3 Synthetic Aperture Radar Altimeter data. For the first time, the simultaneously sensed images from the Ocean and Land Color Instrument, onboard Sentinel-3, were used for training and validation of the classifiers. This product allows to identify leads that are at least 300 meters wide. Applied to data from winter months, the supervised Adaptive Boosting, Artificial Neural Network, Naïve-Bayes, and Linear Discriminant classifiers showed robust results with overall accuracies of up to 92%. The unsupervised Kmedoids classifier produced excellent results with accuracies up to 92.74% and is an attractive classifier when ground truth data is limited. All classifiers perform poorly on summer data, rendering surface classifications that are solely based on altimetry data from summer months unsuitable. Finally, the Adaptive Boosting, Artificial Neural Network, and Bootstrap Aggregation classifiers obtain the highest accuracies when the altimetry observations include measurements from the open ocean.

The Peninsular Malaysia Geodetic Vertical Datum 2000 (PMGVD2000) inherited several deficiencies due to offsets between local datums used, levelling error propagations, land subsidence, sea level rise, and sea level slopes along the southern half of the Malacca Strait on the west coast and the South China Sea in the east coast of the Peninsular relative to the Port Klang (PTK) datum point. To cater for a more reliable elevation-based assessment of both sea level rise and coastal flooding exposure, a new epoch-based height reference system PMGVD2022 has been developed. We have undertaken the processing of more than 30 years of sea level data from twelve tide gauge (TG) stations along the Peninsular Malaysia coast for the determination of the relative mean sea level (RMSL) at epoch 2022.0 with their respective trends and incorporates the quantification of the local vertical land motion (VLM) impact. PMGVD2022 is based on a new gravimetric geoid (PMGeoid2022) fitted to the RMSL at PTK. The orthometric height is realised through the GNSS levelling concept H = h^GNSS–N^fit_PTK–N_RMDT, where N_RMDT is a constant offset due to the relative mean dynamic ocean topography (RMDT) between the fitted geoid at PTK and the local MSL datums along the Peninsular Malaysia coast. PMGVD2022 will become a single height reference system with absolute accuracies of better than ±3 cm and ±10 cm across most of the land/coastal area and the continental shelf of Peninsular Malaysia, respectively.

A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 M_w = 7.5 Palu earthquake (Sulawesi, Indonesia). With a predominantly strike-slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake-induced landslides. In this study we examine the tsunami potential of the co-seismic deformation. To this end, we present a novel geodetic data set of Global Positioning System and multiple Synthetic Aperture Radar-derived displacement fields to estimate a 3D co-seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co-seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co-seismic uplift (>2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co-seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video-derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co-seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic data set constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike-slip faults in transtensional basins.

This article shows the first spectral analysis of fully-focused Synthetic Aperture Radar (FFSAR) altimetry data with the objective of studying backscatter modulations caused by swells. Swell waves distort the backscatter in altimetry radargrams by means of velocity and range bunching. These swell signatures are visible in the tail of the waveform. By locally normalizing the backscatter and projecting the waveforms on an along-/cross-track grid, satellite altimetry can be exploited to retrieve swell information. The analysis of FFSAR spectra is supported by buoy-derived swell-wave spectra of the National Oceanic and Atmospheric Administration network. Using cases with varying wave characteristics, we discuss the altimetry-derived spectra and relate them to what is known from side-looking SAR imaging systems. Besides having a vast amount of additional data for swell-wave analysis, altimeter data can also help us to better understand the side-looking SAR spectra.

Since 8 April 2010 ESA's Earth Explorer mission CryoSat-2 has been measuring marine and land ice thickness variations with a dedicated altimeter. With the effects of a fast-changing climate becoming apparent, it is increasingly important to understand exactly how Earth's ice fields are responding and regulate climate and sea level. It is therefore of utmost importance that the quality of the CryoSat-2 altimeter data meets the highest accuracy and precision level, not only over the ice caps and sea-ice surface but over the oceans as well. The SIRAL altimeter of CryoSat-2 is capable of measuring high-resolution geophysical parameters from the open ocean to the coast. In this paper, we validate the CryoSat-2 geophysical ocean product, Baseline-B (GOP). The analyses focus on long-term monitoring, validation, and cross-calibration of these ocean altimeter data with all the concurrent altimeter data in the Radar Altimeter Database System RADS and with independent in-situ tide gauge measurements from the Permanent Service for Mean Sea Level PSMSL. The objective is to evaluate the stability of the CryoSat-2 measurement system and the identification and explanation of biases and bias drifts. A persistent monitoring of these biases in time is important to establish the data's usefulness for investigation of long-term sea level and ice topography/volume changes. The results constitute the final status of the GOP baseline-B product for use as essential climate variables. GOP ocean data has a -6.3±0.2 cm range bias w.r.t. to all calibrated satellites in RADS and a drift of 0.14 mm yr⁻¹ w.r.t. Jason-2. GOP data has significant wave height and sea state biases close to that of the Jasons’, and seems to be better handling the LRM-SAR transitions than the RADS CryoSat-2 product. GOP data w.r.t. PSMSL tide gauge data has an average correlation of R = 0.83, a mean st. dev. of σ = 6.30 cm, and a drift of 0.11 mm yr⁻¹, equivalent to 40 Gt yr⁻¹ ice sheet mass loss. It is concluded that GOP CryoSat-2 performs better than RADS CryoSat-2, which seems to suffer from a 480-day platform temperature cycle. GOP is also on a par with the altimeter data from the Jason reference missions, and well suited for ocean and climate studies.

Observing the universe in the Ultra-Long Wavelength (ULW) regime has been called the ‘last frontier in astronomy’—real imaging capabilities here are yet to be achieved. Obtaining an image of the sky in this frequency band can be done by employing a swarm of satellites that together act as an interferometer and collect the required imaging information pieces throughout the course of their operational life. Meeting the mission objective is challenging for such a swarm, since this imposes restrictions on the operational environment and the relative position and velocity vectors between the swarm elements. This work proposes an orbit solution in a Heliocentric Earth-Leading Orbit (HELO) for an autonomous CubeSat swarm with chemical thrusters. A distributed formation flying algorithm is used to aid the collection of the required imaging information pieces. Furthermore, the estimated total mission launch mass is reduced by optimising cost functions and finding favourable position and velocity at start of operational life, as well as by finding favourable thrust manoeuvre patterns. The results show that the mission objective—obtaining a 3D map of the Universe in ULW—can be achieved with 68 6U spacecraft (S/C). Moreover, the swarm can remain in a Radio Frequency Interference (RFI) quiet zone of >5 × 10⁶ km, whilst not drifting further than ~ 6.6 × 10⁶ km from Earth for an operational life of one year.

With Mars colonisation becoming a reality for the near future, it is of importance to analyse how crew and cargo can be transported between Earth and a colony on Mars. This article is a feasibility and design study of a launch vehicle whose mission is to shuttle crew and cargo from Low Mars Orbit to a colony on the Martian surface. A single-stage reusable rocket has been selected to fulfil this mission, code-named Charon. The mission profile of such a vehicle was created, leading to a Maximum Growth Allowance (MGA) Delta-V budget of 6.2 km/s. With the mission profile in mind, each subsystem underwent a preliminary design. With reliability and maintainability in mind, subsystems were designed for redundancy and modularity, and an abort system was included for an added level of safety. The iterative design process resulted in a vehicle with a MGA mass of 198.7 tons, capable of transporting 1200 kg of cargo and a crew of 6 people to a 500 km orbit and back. The preliminary design of the vehicle is deemed safe. Following a fault tree analysis, the Single Launch Loss of Mission, Vehicle and Crew (SL-LOM, SL-LOV, SL-LOC) probabilities are computed to be of 0.975%, 0.12%, and 0.079%. Finally, from the vehicle’s constraints on the base, the feasibility of the project has been reflected upon. It is deemed that such a concept is of high interest only when the base is already operational, due to the launch and maintenance infrastructure that it requires, as well as the power it requires from the Martian base.

In recent years, the space market has been pushing towards decreasing costs of launching spacecraft by reusing parts of the launchers. The purpose of this article is to present a feasibility study of a recovery system for the engine and engine frame of an existing, expendable heavy launch vehicle and present recommendations for further research. The concept developed is verified based on the Ariane 6. The recovery of the Vulcain Aft Bay (VuAB) is initialised by separation from the first stage at 157.7 km altitude while travelling at 6930 m/s. The study investigates an inflatable aeroshell for protection and deceleration during re-entry, after which it is proposed to further decelerate the VuAB using drogue parachutes. The final part of the concept entails retrieval of the VuAB by a helicopter in mid-air. To enable a controlled gliding flight during retrieval a parafoil is proposed. At launch, the recovery system will weigh 2789 kg with a payload penalty of 720 kg. The system can be integrated into the existing design of the launcher and will not interfere with nominal operations of the launcher. Implementing the recovery system can reduce the cost per launch of an Ariane 6 by 15%

This paper applies the Fully-Focussed SAR (FF-SAR) algorithm to CryoSat-2 full-bit-rate data to measure water levels of lakes and canals in the Netherlands, and validates these measurements by comparing them to heights measured by gauges. Over Lake IJssel, a medium-sized lake, the FF-SAR height is biased about 6 cm below the gauge height, and a similar bias is found at six sites where CryoSat-2 crosses rivers and canals. The precision of the FF-SAR measurements depends on the extent of multi-looking (incoherent averaging along-track) applied. Over Lake IJssel the precision varies from 4 to 11 cm, decreasing as multi-looking increases. The precision of FF-SAR with 100 m of multi-looking is equivalent to that of the standard delay/Doppler processing, which has an along-track resolution of about 300 m. The width and orientation of rivers and canals limits the maximum available multi-looking. After removing the 6 cm bias, FF-SAR heights of rivers and canals have an accuracy between 2 cm and several decimeters, primarily depending on the presence of other water bodies lying within the cross-track measurement footprint, as these contaminate the waveform. We demonstrate that FF-SAR processing is able to resolve and measure small ditches only a few meters in width. The visibility of these signals depends on the angle at which CryoSat-2 crosses the ditch and on whether or not the ditch remains straight within CryoSat-2’s field of view. In the best-case scenario, straight ditches at nearly 90° to the CryoSat-2 ground track, the ditch signal has high enough signal-to-noise to allow sub-decimeter accuracy of FF-SAR height measurement.

We investigated the sensitivity of fully focused SAR (FF-SAR) processing of Cryosat-2 altimeter data to Earth rotation. Earth’s rotation causes scatterers at varying cross-track locations to have a different relative velocity with respect to the satellite. This second-order effect of Earth rotation on the phase is currently not corrected for in FF-SAR processing of altimetry data. The difference is largest near the poles, where the satellite flies parallel to the equator. Not correcting for the second-order effect yields a parabolic shape in the counter-rotated phase, which increases with the cross-track distance. Its effect is, however, limited by the time-in-view of the scatterer, which is shorter at the edge of the altimeter footprint, and therefore destructive interference will not occur when using Cryosat-2 data. For Cryosat-2, the only expected effect is a reduction in power and along-track resolution in the waveform tail and in the grating lobes. If the FF-SAR processor focuses on one point, and there is a bright scatterer at another, then there is a residual parabolic phase, whose sign and shape depend on the cross-track distance and whether the signal is left or right of the chosen focal point. In theory, if the viewed scene only has few bright coherent scatterers, then it might be possible to determine the cross-track position of each. In practice, however, natural targets are rarely coherent over the integration time.