Search Results (73)

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. Full article

Early-stage dynamic responses of naval structures under underwater explosion shock loads exhibit high-frequency, intense amplitude fluctuations and short durations, serving as critical factors for the development of plastic deformation and other damage characteristics. These structural dynamics demonstrate prominent nonlinear and non-stationary features. This study focuses on the nonlinear evolutionary patterns of early-stage plastic shock responses in underwater explosion-impacted ship structures. Utilizing phase space reconstruction, unimodal mapping, and symbolic dynamics theory, we analyze the nonlinear and non-stationary characteristics along with their evolutionary patterns in experimental data. First, scaled model experiments under varying shock factors were conducted based on a stiffened cylindrical shell prototype, investigating the spatiotemporal evolution of nonlinear and non-stationary dynamic responses under different shock loads while characterizing their uncertainty features. Second, model tests were performed on deck-type cabin structures and plate frameworks derived from a naval vessel’s deck prototype, further analyzing the evolutionary patterns of early-stage plastic dynamic responses and verifying the method’s effectiveness and universality. Research findings indicate that (1) early-stage plastic shock responses of ships under underwater explosions exhibit multiple dynamical behaviors including chaotic motion, periodic motion, and quasi-periodic motion, and (2) during the initial plastic phase, orbital parameters approximate 0.8, providing guidance for test condition setup and initial parameter selection in underwater explosion experiments on naval structures. Full article

The 4-body equations of motion are derived in our previously published paper. Here we prove the existence–uniqueness of a periodic solution by applying the fixed-point method for a suitable introduced operator. To apply the fixed-point theorem, we need to derive appropriate analytical inequalities for the right-hand sides of the equations that ensure that the operator for periodic solutions maps the set of periodic functions into itself. In this way, we prove the existence of the Bohr–Sommerfeld orbits for the 4-body problem in the relativistic case. That allows us to estimate the minimal distances between the electrons on the first and second Bohr–Sommerfeld stationary states. A natural example of such a problem is the Lithium atom, which has three electrons orbiting the nucleus. Full article

Effective energy management in Low Earth Orbit satellites is critical, as inefficient energy management can significantly affect mission objectives. The dynamic and harsh space environment further complicates the development of effective energy management strategies. To address these challenges, we propose a Deep Reinforcement Learning approach using Deep-Q Network to develop an adaptive energy management framework for Low Earth Orbit satellites. Compared to traditional techniques, the proposed solution autonomously learns from environmental interaction, offering robustness to uncertainty and online adaptability. It adjusts to changing conditions without manual retraining, making it well-suited for handling modeling uncertainties and non-stationary dynamics typical of space operations. Training is conducted using a realistic satellite electric power system model with accurate component parameters and single-orbit power profiles derived from real space missions. Numerical simulations validate the controller performance across diverse scenarios, including multi-orbit settings, demonstrating superior adaptability and efficiency compared to conventional Maximum Power Point Tracking methods. Full article

By “nethotron”, from the ancient Greek verb for “to spin”, it is meant here a natural or artificial rotating object, like a pulsar or an artificial satellite, whose rotational axis is cumulatively displaced by the post-Newtonian static (gravitoelectric) and stationary (gravitomagnetic) components of the gravitational field of some massive body around which it freely moves. Until now, both relativistic effects have been measured only by the dedicated space-based mission Gravity Probe B in the terrestrial environment. It detected the gravitoelectric de Sitter and gravitomagnetic Pugh–Schiff spin precessions of four superconducting gyroscopes accumulated within a year after about 50 years from conception to completion of data analysis at a cost of 750 million US dollars to $0.3$ and 19 percent accuracy, respectively. The perspectives to measure them with Earth’s long-lived laser-ranged geodetic satellites, like those of the LAGEOS family or possibly one or more of them to be built specifically from scratch, and pulsars orbiting the supermassive black hole in the Galactic Centre, yet to be discovered, are preliminarily investigated. The double pulsar PSR J0737-3039A/B is examined as well. Full article

Antibiotic pollution, particularly via tetracycline (TC), poses significant environmental risks due to its recalcitrance and potential to induce antibiotic resistance. This study employed density functional theory (DFT) and transition state theory (TST) to investigate TC degradation by hydroxyl radicals (·OH), focusing on hydrogen atom transfer (HAT) and radical adduct formation (RAF) pathways. Geometry optimizations and vibrational analysis validated stationary points, while intrinsic reaction coordinate (IRC) calculations confirmed transition states. Key findings reveal that RAF pathways exhibit lower activation barriers (1.23–30.33 kJ/mol) and greater exothermicity (−164.42 kJ/mol) compared to HAT pathways (3.51–42.04 kJ/mol, −109.58 kJ/mol), making them kinetically and thermodynamically dominant. Frontier molecular orbital (FMO) analysis links HAT to TC’s HOMO (π-orbital character on aromatic rings) and RAF to its LUMO (electrophilic sites). Rate constants calculated at 298 K (TST with Wigner correction) confirm RAF’s kinetic superiority (up to 7.0 × 10¹¹ s⁻¹), surpassing HAT’s fastest pathway (6.2 × 10¹¹ s⁻¹). These insights advance the understanding of TC degradation mechanisms and help with the design of efficient photocatalytic oxidation processes for antibiotic removal. Full article

NASA’s Juno mission, involving a pioneering spacecraft the size of a basketball court, has been instrumental in observing Jupiter’s atmosphere and surface from orbit since it reached the intended orbit. Over its first decade of operation, Juno has provided unprecedented insights into the solar system’s origins through advanced remote sensing and technological innovations. This study focuses on change detection in terms of Juno’s trajectory, leveraging cutting-edge data computing techniques to analyze its orbital dynamics. Utilizing 3D position and velocity time series data from NASA, spanning 11 years and 5 months (August 2011 to January 2023), with 5.5 million samples at 1 min accuracy, we examine the spacecraft’s trajectory modifications. The instantaneous average acceleration, jerk, and snap are computed as approximations of the first, second, and third derivatives of velocity, respectively. The Hilbert transform is employed to visualize the spectral properties of Juno’s non-stationary 3D movement, enabling the detection of extreme events caused by varying forces. Two unsupervised machine learning algorithms, DBSCAN and OPTICS, are applied to cluster the sampling events in two 3D state spaces: (velocity, acceleration, jerk) and (acceleration, jerk, snap). Our results demonstrate that the OPTICS algorithm outperformed DBSCAN in terms of the outlier detection accuracy across all three operational phases (OP1, OP2, and OP3), achieving accuracies of 99.3%, 99.1%, and 98.9%, respectively. In contrast, DBSCAN yielded accuracies of 98.8%, 98.2%, and 97.4%. These findings highlight OPTICS as a more effective method for identifying outliers in elliptical orbit data, albeit with higher computational resource requirements and longer processing times. This study underscores the significance of advanced machine learning techniques in enhancing our understanding of complex orbital dynamics and their implications for planetary exploration. Full article

Accurate prediction of the on-orbit positions of Low Earth Orbit (LEO) satellites is essential for mission success, operational efficiency, and safety. Nevertheless, the non-stationary nature of orbital data and sensor noise presents significant challenges for accurate prediction. To address these challenges, we propose a novel forecasting model, EMD-ICA-DLinear, which combines trend-residual representation with EMD-ICA in an innovative manner. By integrating the TSR (Trend, Seasonality, and Residual) framework with the EMD-ICA dual perspective, this approach provides a comprehensive understanding of time series data and outperforms traditional models in capturing subtle nonlinear relationships. When predicting the orbital position of the Fengyun-3C satellite, the model uses MSE and MAE as evaluation metrics. Experimental results indicate that the proposed EMD-ICA-DLinear hybrid model achieves MSE and MAE values of 0.1101 and 0.1567, respectively, when predicting the orbital position of the Fengyun-3C satellite 6 h in advance, representing reductions of 37.87% and 19.85% compared to the best baseline model, TimesNet. This advancement enhances satellite orbit prediction accuracy, supports operational stability, and enables timely adjustments, thereby improving mission efficiency and safety. Full article

Phycocyanobilin (PCB) is a small chromophore found in certain phycobiliproteins, such as phycocyanins (PCs) and allophycocyanins (APCs). PCB, along with other phycobilins (PBs) and intermediates such as biliverdin (BV) or phycoerythrobilin (PEB), is attracting increasing biotechnological interest due to its fluorescent and medicinal properties that allow potential applications in biomedicine and the food industry. This study aims to optimize PCB synthesis in Escherichia coli BL21 (DE3) and scale the process to a pre-industrial level. Parameters such as optimal temperature, inducer concentration, initial OD₆₀₀, and stirring speed were analyzed in shake flask cultures to maximize PCB production. The best results were obtained at a temperature of 28 °C, an IPTG concentration of 0.1 mM, an initial OD₆₀₀ of 0.5, and an orbital shaking speed of 260 rpm. Furthermore, the optimized protocol was scaled up into a 2 L bioreactor batch, achieving a maximum PCB concentration of 3.8 mg/L. Analysis of the results revealed that biosynthesis of exogenous PBs in Escherichia coli BL21 (DE3) is highly dependent on the metabolic burden of the host. Several scenarios, such as too rapid growth, high inducer concentration, or mechanical stress, can advance entry into the stationary phase. That progressively halts pigment synthesis, leading, in some cases, to its excretion into the growth media and ultimately triggering rapid degradation by the host. These conclusions provide a promising protocol for scalable PCB production and highlight the main biotechnological challenges to increase the yields of the process. Full article

The operation of many queueing systems is adequately described by the structured multidimensional continuous-time Markov chains. The most well-studied classes of such chains are level-independent Quasi-Birth-and-Death processes, $GI/M/1$ type and $M/G/1$ type Markov chains, generators of which have the block tri-diagonal, lower- and upper-Hessenberg structure, respectively. All these classes assume that the matrices of transition rates are quasi-Toeplitz. This property greatly simplifies their analysis but makes them inappropriate for the study of many important systems, e.g., retrial queues with a retrial rate depending on the number of customers in orbit, queues with impatient customers, etc. The importance of such systems attracts significant interest to their analysis. However, in the literature, there is a methodological gap relating to the ergodicity condition of the corresponding Markov chains. To fulfill this gap and facilitate the analysis of a wide range of such systems, we show that under non-restrictive assumptions, the following hold true: (i) if the customers can balk or are impatient or non-persistent, then the Markov chain describing the behavior of the system belongs to the class of asymptotically quasi-Toeplitz Markov chains; (ii) this chain is ergodic; (iii) known algorithms can be applied for the calculation of the stationary distribution of the corresponding queueing system. Full article

A solar sail is a propellantless propulsion system that allows a spacecraft to use solar radiation pressure as a propulsive source for planetary and deep space missions that would be difficult, or even unfeasible, to accomplish with more conventional thrusters, either chemical or electric. A challenging application for these fascinating propulsion systems is a heliocentric mission that requires a displaced non-Keplerian orbit (DNKO), that is, a solar sail-induced closed trajectory in which the orbital plane does not contain the Sun’s center of mass. In fact, thanks to the pioneering work of McInnes, it is known that a solar sail is able to reach and maintain a family of heliocentric DNKOs of given characteristics. The aim of this paper is to analyze the properties of Mars-synchronous circular DNKOs, which have an orbital period matching that of the planet for remote sensing applications. In fact, those specific displaced orbits allow a scientific probe to continuously observe the high-latitude regions of Mars from a quasi-stationary position relative to the planet. In this context, this paper also analyzes the optimal (i.e., the minimum-time) heliocentric transfer trajectory from the Earth to circular DNKOs in two special mission scenarios taken as a reference. Full article

In response to the need for a space security situation assessment during orbit, the multi-satellite space environmental risk prediction and early warning system is based on the detection results of the space weather payload of the Fengyun 4A and 4B satellites, as well as the prediction results of the National Space Weather Center, for the first time. By comprehensively utilizing some open-source data, it is the first time that we have achieved a 24 h advanced prediction of the space environment high-energy proton, low-energy particle, and high-energy electron risks for the safety of the Fengyun-series high-orbit satellites, and a real-time warning of satellite single-event upset, surface charging, and deep charging risks. The automation system has preliminarily achieved an intelligent space risk assessment for the safety of multiple stationary meteorological satellites, effectively improving the application efficiency of the space environmental data and the products of Fengyun-series satellites. The business status is stable in operation, and the resulting error between the predicted results of various risk indices and the measured data was less than one level. The warning accuracy was better than 90%. This article uses the system for the first time, to use Fengyun satellite data to, accurately and in a timely manner, predict and warn us about the low-energy particles and surface charging high-risk levels of the Fengyun 4A and 4B satellites during the typical space weather event on 21 April 2023, in response to the impact of complex spatial environmental factors on the safety of Fengyun-series high-orbit satellites. The construction and operation of a multi-satellite space environmental risk prediction and early warning system can provide a reference for the safety work of subsequent satellite ground system operations. Full article

Imaging maritime targets requires a high resolution and wide swath (HWRS) in a synthetic aperture radar (SAR). When operated with a variable pulse repetition interval (PRI), a staggered SAR can realize HRWS imaging, which needs to be reconstructed due to echo pulse loss and a nonuniformly sampled signal along the azimuth. The existing reconstruction algorithms are designed for stationary scenes in a staggered SAR mode, and thus, produce evident image defocusing caused by complex target motion for moving targets. Typically, the nonuniform sampling and complex motion of maritime targets aggravate the spectrum aliasing in a staggered SAR mode, causing inevitable ambiguity and degradation in its reconstruction performance. To this end, this study analyzed the spectrum of maritime targets in a staggered SAR system through theoretical derivation. After this, a reconstruction method named MBLCFD (Modified Best Linear Unbaised and Complex-Lag Time-Frequency Distribution) is proposed to refocus the blurred maritime target. First, the signal model of the maritime target with 3D rotation accompanying roll–pitch–yaw movement was established under the curved orbit of the satellite. The best linear unbiased (BLU) method was modified to alleviate the coupling of nonuniform sampling and target motion. A precise SAR algorithm was performed based on the method of inverse reversion to counteract the effect of a curved orbit and wide swath. Based on the hybrid SAR/ISAR technique, the complex-lag time-frequency distribution was exploited to refocus the maritime target images. Simulations and experiments were carried out to verify the effectiveness of the proposed method, providing precise refocusing performance in staggered mode. Full article

The application of space robotic manipulators and heightened autonomy for In-Orbit Servicing (IOS) represents a paramount pursuit for leading space agencies, given the substantial threat posed by space debris to operational satellites and forthcoming space endeavors. This work presents a guidance algorithm based on Deep Reinforcement Learning (DRL) to solve for space manipulator path planning during the motion-synchronization phase with the mission target. The goal is the trajectory generation and control of a spacecraft equipped with a 7-Degrees of Freedom (7-DoF) robotic manipulator, such that its end effector remains stationary with respect to the target point of capture. The Proximal Policy Optimization (PPO) DRL algorithm is used to optimize the manipulator’s guidance law, and the autonomous agent generates the desired joint rates of the robotic arm, which are then integrated and passed to a model-based feedback linearization controller. The agent is first trained to optimize its guidance policy and then tested extensively to validate the results against a simulated environment representing the motion synchronization scenario of an IOS mission. Full article

This paper is devoted to the analysis of fluctuations in the solar wind plasma and interplanetary magnetic field parameters observed by Solar Orbiter and WIND spacecraft at different scales ranging from ~10³ to 10⁷ km. We consider two long data intervals where the distances between the spacecraft are 0.1 and 0.5 AU, respectively, and they are located close to the Sun–Earth line. Transformation of the fluctuation’s properties on the way from the Sun to Earth is analyzed for different types of solar wind associated with quasi-stationary and transient solar phenomena. The time series of bulk speed are shown to undergo a slight modification, even for large spacecraft separation, while the time series of the interplanetary magnetic field magnitude and components as well as proton density may be transformed even at a relatively short distance. Though the large-scale solar wind structures propagate the distance up to 0.5 AU without significant change, local structures at smaller scales may be modified. The statistical properties of the fluctuations such as relative standard deviation or probability distribution function and its moments remain nearly unchanged at different distances between the two spacecraft and are likely to depend mostly on the type of the solar wind. Full article