Current Issue : January-March Volume : 2026 Issue Number : 1 Articles : 5 Articles
Time dilation is a measurable change in the passage of time caused by differences in gravitational potential, a key prediction of general relativity. Recent advances in atomic clock precision allow such differences to be detected over small separations relative to that gravitational potential. This capability introduces a new approach to satellite attitude and altitude determination, independent of line-of-sight, optical, or magnetic-field-based sensing. This method could be particularly valuable for planetary landing and navigation missions, including those on the Moon and Mars, where traditional reference systems may be unavailable or unreliable....
The geostationary orbit (GEO), about 35,786 km above the Earth’s equator, hosts high-value satellites like communication, meteorological, and navigation ones. Real-time detection of geostationary orbit targets is crucial for orbital resource safety and satellite operation. Large field-of-view (FOV) telescopes can observe many such targets but face technical bottlenecks due to their optical systems, such as weak light-gathering capability, stellar interference, and complex stray light. This paper analyzes the apparent motion differences between stars and geostationary orbit targets based on the telescope’s staring mode. Stars move overall in images while GEO targets are relatively stationary. A minimum value stacking (Min-Stacking) method is proposed to suppress stars, improving GEO targets’ signal-to-noise ratio. With the global threshold segmentation algorithm, fast and accurate target extraction is achieved. Experiments show the method has high detection rates, overcomes interference, and features simplicity and real-time performance, with important application value....
The interstellar object 3I/ATLAS is expected to arrive at a distance of 53.56(±0.45) million km (0.358 ± 0.003 au) from Jupiter on 16 March 2026. We show that applying a total thrust ΔV of 2.6755 km s−1 to the lower perijove on 9 September 2025 and then executing a Jupiter Oberth Maneuver can bring the Juno spacecraft from its orbit around Jupiter to intercept the path of 3I/ATLAS on 14 March 2026. We further show that it is possible for Juno to come much closer to 3I/ATLAS (∼27 million km) with 110 kg of remaining propellant, merely 5.4% of the initial fuel reservoir. We find that for low available ΔV, there is no particular benefit in the application of a double impulse (for example, to reach ∼27 million km from 3I/ATLAS); however, if Juno has a higher ΔV capability, there is a significant advantage of a second impulse, typically saving propellant by a factor of a half. A close fly-by might allow us to probe the nature of 3I/ATLAS far better than telescopes on Earth....
This study investigates the heat transfer characteristics of high-temperature alumina droplets impacting carbon–phenolic ablative materials in solid rocket motors using the Volume of Fluid (VOF) method. Simulations under varied droplet diameters, impact velocities, wall temperatures, and accelerations were carried out, and the simulation method was validated against experimental data. Results show that heat flux drops rapidly from 20 MW/m2 to below 5 MW/m2 after the non-dimensional time t∗ = 0.5, due to solidified layer formation at the droplet bottom, which shifts heat transfer from convection to conduction and increases thermal resistance. The solidified layer is thicker at the sides and thinner in the center, caused by weaker heat transfer in the thinner side regions. Acceleration is found to have a negligible influence on impact dynamics within wall temperatures of 25 ◦C to 1000 ◦C, as potential energy conversion during spreading is insignificant compared to kinetic energy. Thus, droplet–wall heat transfer dominates the process. These findings provide critical thermal boundaries for ablation modeling and improve design guidance for SRMs....
An increased level of autonomy is attractive above all in the framework of proximity operations, and researchers are focusing more and more on artificial intelligence techniques to improve spacecraft’s capabilities in these scenarios. This work presents an autonomous AI-based guidance algorithm to plan the path of a chaser spacecraft for the map reconstruction of an artificial uncooperative target, coupled with Model Predictive Control for the tracking of the generated trajectory. Deep reinforcement learning is particularly interesting for enabling spacecraft’s autonomous guidance, since this problem can be formulated as a Partially Observable Markov Decision Process and because it leverages domain randomization well to cope with model uncertainty, thanks to the neural networks’ generalizing capabilities. The main drawback of this method is that it is difficult to verify its optimality mathematically and the constraints can be added only as part of the reward function, so it is not guaranteed that the solution satisfies them. To this end a convex Model Predictive Control formulation is employed to track the DRL-based trajectory, while simultaneously enforcing compliance with the constraints. Two neural network architectures are proposed and compared: a recurrent one and the more recent transformer. The trained reinforcement learning agent is then tested in an end-to-end AI-based pipeline with image generation in the loop, and the results are presented. The computational effort of the entire guidance and control strategy is also verified on a Raspberry Pi board. This work represents a viable solution to apply artificial intelligence methods for spacecraft’s autonomous motion, still retaining a higher level of explainability and safety than that given by more classical guidance and control approaches....
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