Search Results (51)

Orbit determination for non-cooperative low Earth orbit (LEO) objects undergoing continuous low-thrust maneuvers remains a significant challenge, particularly for large satellite constellations like Starlink. This paper presents a method that integrates the unscented transformation into a batch filtering framework with an optimized rho-minimum sigma points sampling strategy. The proposed approach uses a reduced dynamics model that considers Earth’s non-spherical gravity and models the combined effects of low-thrust and atmospheric drag as an equivalent along-track acceleration. Numerical simulations under different measurement noise levels, initial state uncertainties, and across multiple satellites confirm the method’s reliable convergence and favorable accuracy, even in the absence of prior knowledge of the along-track acceleration. The method consistently converges within 10 iterations and achieves 24 h position predictions with root mean square errors of less than 3 km under realistic noise conditions. Additional validation using a higher-fidelity model that explicitly accounts for atmospheric drag demonstrates improved accuracy and robustness. The proposed method can provide accurate orbit knowledge for space situational awareness associated with continuously maneuvering Starlink satellites. Full article

A novel satellite architecture and deployment method is proposed to reduce the logistical cost and complexity of launching and dispersing satellite constellations. The architecture consists of a primary satellite that separates into multiple smaller units, which are subsequently dispersed using differential drag. An algorithm is developed to determine the required disengagement velocities and optimal timing for separation maneuvers. Two case studies with orbital simulations demonstrate the feasibility of this approach for constellation deployment and phasing. The results indicate that while mission-specific factors influence deployment dynamics, informed selection of the disengagement velocities is crucial for minimizing phase times and mitigating potential delays. The findings confirm the feasibility of the proposed architecture and dispersal method, offering a cost-effective alternative to traditional deployment strategies for future satellite constellations. Full article

This paper addresses the selection and justification of ephemeris parameters to be broadcast in a LEO-PNT navigation message. The temporal evolution of LEO orbital elements is analyzed, proving that the GPS/GAL model needs to evolve to cope with LEO orbit dynamics and to ensure high-accuracy ephemeris. In addition, the ephemeris fitting process is performed systematically for different sets of parameters allowing the most convenient parameter combinations to be determined. If adequate parameters are included in an ephemeris model, the fitting error tends to reduce. Beyond ephemeris parametrization, the length of the fitting interval significantly influences the achievable accuracy—for short fitting intervals of 5–10 min with an optimal set of ephemeris parameters, a SISRE at WUL in the order of 1 to 7 mm is obtained. Full article

Enhanced real-time onboard orbit determination for low-Earth-orbit satellites is essential for autonomous spacecraft operations. However, the accuracy of such systems is often limited by signal propagation delays between GPS satellites and the user spacecraft. These delays, primarily due to Earth’s rotation and ionospheric effects become particularly significant in high-dynamic LEO environments, leading to considerable errors in range and range rate measurements, and consequently, in position and velocity estimation. To mitigate these issues, this paper proposes a real-time orbit determination algorithm that applies Earth rotation correction and dual-frequency (L1 and L2) ionospheric compensation to raw GPS measurements. The enhanced orbit determination method is processed directly in the Earth-centered Earth-fixed frame, eliminating repeated coordinate transformations and improving integration with ground-based systems. The proposed method employs a reduced-dynamic orbit determination strategy to balance model fidelity and computational efficiency. A predictive correction model is also incorporated to compensate for GPS signal delays under dynamic motion, thereby enhancing positional accuracy. The overall algorithm is embedded within an extended Kalman filter framework, which assimilates the corrected GPS observations with a stochastic process noise model to account for dynamic modeling uncertainties. Simulation results using synthetic GPS measurements, including pseudoranges and pseudorange rates from a dual-frequency spaceborne receiver, demonstrate that the proposed method provides a significant improvement in orbit determination accuracy compared to conventional techniques that neglect signal propagation effects. These findings highlight the importance of performing orbit estimation directly in the Earth-centered, Earth-fixed reference frame, utilizing pseudoranges that are corrected for ionospheric errors, applying reduced-dynamic filtering methods, and compensating for signal delays. Together, these enhancements contribute to more reliable and precise satellite orbit determination for missions operating in low Earth orbit. Full article

Efficient data transmission in low Earth orbit (LEO) satellite networks is critical for supporting real-time global communication, Earth observation, and numerous data-intensive space missions. A fundamental challenge in these networks involves solving the maximum flow problem, which determines the optimal data throughput across highly dynamic topologies with limited onboard energy and data processing capability. Traditional algorithms often fall short in these environments due to their high computational costs and inability to adapt to frequent topological changes or fluctuating link capacities. This paper introduces an accelerated maximum flow algorithm specifically designed for dynamic LEO networks, leveraging a prediction-enhanced approach to improve both speed and adaptability. The proposed algorithm integrates a novel energy-time expanded graph (e-TEG) framework, which jointly models satellite-specific constraints including time-varying inter-satellite visibility, limited onboard processing capacities, and dynamic link capacities. In addition, a learning-augmented warm-start strategy is introduced to enhance the Ford–Fulkerson algorithm. It generates near-optimal initial flows based on historical network states, which reduces the number of augmentation steps required and accelerates computation under dynamic conditions. Theoretical analyses confirm the correctness and time efficiency of the proposed approach. Evaluation results validate that the prediction-enhanced approach achieves up to a 32.2% reduction in computation time compared to conventional methods, particularly under varying storage capacity and network topologies. These results demonstrate the algorithm’s potential to support high-throughput, efficient data transmission in future satellite communication systems. Full article

As the number of satellites and amount of space debris in Low-Earth orbit (LEO) increase, high-precision orbit determination is crucial for ensuring the safe operation of spacecraft and maintaining space situational awareness. However, ground-based optical observations are constrained by limited arc-segment angular data and dynamic noise interference, and the traditional Extended Kalman Filter (EKF) struggles to meet the accuracy and robustness requirements in complex orbital environments. To address these challenges, this paper proposes a Bayesian Adaptive Extended Kalman Filter (BAEKF), which synergistically optimizes track determination through dynamic noise covariance adjustment and Bayesian a posteriori probability correction. Experiments demonstrate that the average root mean square error (RMSE) of BAEKF is reduced by 34.7% compared to the traditional EKF, effectively addressing EKF’s accuracy and stability issues in nonlinear systems. The RMSE values of UKF, RBFNN, and GPR also show improvement, providing a reliable solution for high-precision orbital determination using optical observation. Full article

This study examines the differences in performance between orbitally shaken bioreactors (OSBs) and stirred tank bioreactors (STBs) in Chinese Hamster Ovary (CHO) cell perfusion culture in response to the growing market demand for monoclonal antibodies (mAbs). Although OSBs demonstrated higher cell densities, a notable reduction in specific antibody production rates was observed during the mid-to-late phases of the culture compared with STBs. To elucidate the underlying mechanisms, the rheological behaviour of high-density cell suspensions in both reactor types was initially characterised, confirming their adherence to the Sisko fluid model. Computational Fluid Dynamics (CFD) analysis revealed the influence of these rheological properties on the shear stress distribution and mass transfer. This analysis identified the key limiting factors for achieving higher cell densities: mass transfer efficiency in OSBs and shear stress in STBs. Using an Euler–Lagrangian cell-tracking methodology to analyse cellular “lifelines”, it was determined that OSBs exhibited approximately twice the number and frequency of shear stress peak occurrences compared to STBs. This persistent mechanical stimulation likely contributes to the reduced specific antibody production rates observed. This comprehensive investigation not only clarifies the comparative advantages and limitations of different bioreactor types in perfusion culture but also provides a robust theoretical basis and technical guidance for informed reactor selection, optimisation, and scale-up in industrial production environments. Full article

For the mission requirements of the preliminary design phase for kinetic impact deflection of asteroids, an improved pork-chop plot design method is proposed which comprehensively considers both engineering constraints and deflection effectiveness. This method enables the visualization of engineering constraints, such as launch site, launch vehicle, and impact visibility, as well as the deflection distance after impact, all within a single plot. It provides a set of initial values that meet the requirements within the designated window for subsequent trajectory correction, based on different mission needs. Based on the patched conic technique, this paper first establishes a dynamical model for the spacecraft’s trajectory to the asteroid and then determines the parameters for both Earth departure and asteroid impact by solving the Lambert problem. Then, based on the departure parameters, the expression for Earth parking orbit escape is derived, and the constraints of rocket coasting time and launch site latitude, respectively, are transformed into parameter constraints on the argument of perigee and launch declination. Based on the impact parameters, an asteroid deflection dynamics model is established to compute the asteroid’s apparent magnitude and deflection distance. Finally, the improved pork-chop plot is generated using the aforementioned models. The plot comprehensively displays the optimized target parameters and engineering constraint parameters throughout the entire process, from launch vehicle departure to the post-impact deflection distance, within the given launch window. This provides initial values that satisfy both engineering constraints and mission requirements for the trajectory design of an in-orbit kinetic impactor asteroid deflection test mission. Compared to other trajectory design methods that provide only a single trajectory, the improved pork-chop plot enables a rapid, intuitive, and comprehensive visualization of a cluster of launch trajectories within the feasible window that satisfy engineering constraints. This approach reduces the number of iterations required for matching the deep-space transfer trajectory with the launch vehicle injection phase from more than five to one. The proposed method can serve as a valuable reference for target selection and trajectory optimization in in-orbit validation missions for kinetic impact deflection of asteroids. Full article

The deployment of the HY-2B/2C/2D satellite constellation marks a significant advancement in China’s marine dynamic environmental satellite program, forming a robust three-satellite network. All satellites are equipped with the “HY2_Receiver”, an indigenous technological achievement. Precise orbit determination using this receiver is critical for monitoring dynamic oceanic parameters such as sea surface wind fields and heights. This study presents a detailed analysis and comparison of the GPS data quality from the HY-2B/2C/2D satellites, emphasizing the impact of phase center variation (PCV) model corrections on orbit accuracy, with a particular focus on high-precision reduced-dynamic orbit determination. The experimental results demonstrate that the GPS data from the satellites exhibit consistent satellite visibility and minimal multipath errors, confirming the reliability and stability of the receivers. Incorporating PCV model corrections significantly enhances orbit accuracy, achieving improvements of approximately 0.3 cm. Compared to DORIS-derived orbits from the Centre National d’Études Spatiales (CNES), the GPS-derived reduced-dynamic orbits consistently reach radial accuracies of 1.5 cm and three-dimensional accuracies of 3 cm. Furthermore, validation using Satellite Laser Ranging (SLR) data confirms orbit accuracies better than 3.5 cm, with 3D root mean square (RMS) accuracies exceeding 3 cm in the radial (R), along-track (T), and cross-track (N) directions. Notably, the orbit determination accuracy remains consistent across all satellites within the HY-2B/2C/2D constellation. This comprehensive analysis highlights the consistent and reliable performance of the indigenous “HY2_Receiver” in supporting high-precision orbit determination for the HY-2B/2C/2D constellation, demonstrating its capability to meet the rigorous demands of marine dynamic environmental monitoring. Full article

Low-performing GPS receivers, often used in challenging scenarios such as attitude maneuver and attitude rotation, are frequently encountered for micro–nano satellites. To address these challenges, this paper proposes a modified robust adaptive hierarchical filtering algorithm (named IARKF). This algorithm leverages robust adaptive filtering to dynamically adjust the distribution of innovation vectors and employs a fading memory weighted method to estimate measurement noise in real time, thereby enhancing the filter’s adaptability to dynamic environments. A segmented adaptive filtering strategy is introduced, allowing for flexible parameter adjustment in different dynamic scenarios. A micro–nano satellite equipped with a miniaturized dual-frequency GPS receiver is employed to demonstrate precise orbit determination capabilities. On-orbit GPS data from the satellite, collected in two specific scenarios—slow rotation and Earth-pointing stabilization—are analyzed to evaluate the proposed algorithm’s ability to cope with weak GPS signals and satellite attitude instability as well as to assess the achievable orbit determination accuracy. The results show that, compared to traditional Extended Kalman Filters (EKF) and other improved filtering algorithms, the IARKF performs better in reducing post-fit residuals and improving orbit prediction accuracy, demonstrating its superior robustness. The three-axes orbit determination internal consistency precision can reach the millimeter level. This work explores a feasible approach for achieving high-performance orbit determination in micro–nano satellites. Full article

In chaos control, one usually seeks to stabilize the unstable periodic orbits (UPOs) that densely inhabit the attractors of many chaotic dynamical systems. These orbits collectively play a significant role in determining the dynamics and properties of chaotic systems and are said to form the skeleton of the associated attractors. While UPOs are insightful tools for analysis, they are naturally unstable and, as such, are difficult to find and computationally expensive to stabilize. An alternative to using UPOs is to approximate them using cupolets. Cupolets, a name derived from chaotic, unstable, periodic, orbit-lets, are a relatively new class of waveforms that represent highly accurate approximations to the UPOs of chaotic systems, but which are generated via a particular control scheme that applies tiny perturbations along Poincaré sections. Originally discovered in an application of secure chaotic communications, cupolets have since gone on to play pivotal roles in a number of theoretical and practical applications. These developments include using cupolets as wavelets for image compression, targeting in dynamical systems, a chaotic analog to quantum entanglement, an abstract reducibility classification, a basis for audio and video compression, and, most recently, their detection in a chaotic neuron model. This review will detail the historical development of cupolets, how they are generated, and their successful integration into theoretical and computational science and will also identify some unanswered questions and future directions for this work. Full article

Haiyang-2A (HY-2A) is the first marine dynamic environment satellite established by China, which has made significant contributions to the marine scientific research field. It carries the satellite-based GPS receiver named HY2, which was independently developed by China. It is an experimental satellite-borne GPS receiver for low earth orbit satellites, and during its operational period in orbit, the satellite-borne GPS data are not made accessible to the public. Therefore, this paper assesses the quality of HY-2A satellite-borne GPS data based on indicators such as satellite visibility, multipath effect, and ionospheric delay. The results indicate that the data acquired by the HY2 receiver are of high quality. The precise orbit determination (POD) uses the reduced-dynamic (RD) method. The adjustment effects of the pseudo-stochastic pulse time interval and a priori sigma on POD are analyzed, and the antenna phase center variation (PCV) is estimated using the direct method and residual method. Furthermore, this paper investigates the impact of PCV models with different resolutions (10° × 10° and 5° × 5°) on satellite orbit determination. To evaluate the orbit precision, three methods are used for validation, including carrier phase residual analysis, external precise science orbit (PSO) validation, and SLR three-dimensional (3D) validation, respectively. The results indicate that the highest orbit precision is achieved when the pseudo-stochastic pulse time interval is configured to 15 min, with the a priori sigma of 1 × 10⁻⁸ m/s². The orbit carrier phase residuals reach the millimeter level. The 10° × 10°PCV model was estimated using the direct method and residual method, respectively; the root mean square of the external orbit validation for both methods show a millimeter-level improvement. The results obtained from the direct method and residual method are comparable. The resolution is increased from 10° to 5°, and the improvement in orbital precision is relatively small. The results obtained from the SLR 3D validation are consistent with those from the external PSO validation. The experimental results contribute valuable information for the POD of the HY2 series satellites. Full article

Space-based opportunistic positioning is a crucial component of resilient positioning, navigation, and timing (PNT) systems, and it requires the acquisition of orbit information for non-cooperative low Earth orbit (LEO) satellites. Traditional methods for orbit determination (OD) of non-cooperative LEO satellites have difficulty in achieving a balance between reliability, hardware costs, and availability duration. To address these challenges, this study proposes a framework for single-station orbit determination of non-cooperative LEO satellites. By utilizing signals of opportunity (SOPs) captured by a single ground station, the system performs initial orbit determination (IOD), precise orbit determination (POD), and orbit prediction (OP), enabling the long-term determination of satellite positions and velocities. Under the proposed framework, the reliability and real-time performance are dependent on the initial orbit determination and the orbit calculation based on the dynamical model. To achieve initial orbit determination, a three-step algorithm is designed. (1) An improved search method is employed to estimate a coarse orbit using single-pass Doppler measurements. (2) Data association is conducted to obtain multi-pass Doppler observations. (3) The least squares (LS) is implemented to determine the initial orbit using the associated multi-pass Doppler measurements and the coarse orbit. Additionally, to enhance computational efficiency, two fast orbit calculation algorithms are devised. These algorithms leverage the numerical stability of the Runge–Kutta integrator to reduce computations and exploit the strong correlation among nearby time intervals of orbits with small eccentricities to minimize redundant calculations, thereby achieving orbit calculation efficiently. Finally, through positioning experiments, the determined orbits are demonstrated to have accuracy comparable to that of two-line elements (TLE) updated by the North American Aerospace Defense Command (NORAD). Full article

With the expansion of user scale in LEO satellite networks, unbalanced regional load and bursty network traffic lead to the problem of load disequilibrium. A distributed hops-based back-pressure (DHBP) routing is proposed. DHBP theoretically derives a fast solution for the minimum end-to-end propagation hops between satellite nodes in inclined-orbit LEO satellite networks; hence, link weights are determined based on remaining hops between the next hop and destination satellites. In order to control the number of available retransmission paths, the permitted propagation region is restricted to a rectangular region consisting of source-destination nodes to reduce the propagation cost. Finally, DHBP is designed distributedly, to realize a dynamic selection of the shortest link with low congestion and balanced traffic distribution without obtaining the whole network topology. Network simulation results demonstrate that DHBP has higher throughput and lower delay under high load conditions compared with state-of-the-art routing protocols. Full article

Positioning services based on GNSS (Global Navigation Satellite Systems) have been using MEO satellites designed to guarantee Earth global coverage for decades. This satellite distribution is sometimes complemented with satellites in Inclined Geosynchronous (IGSO) and Geostationary (GEO) Orbits to improve satellite visibility in particular service areas. During recent years, with the advancements and reduction in costs in the deployment of LEO (Low Earth Orbit) constellations, the opportunity of using LEO satellites for PNT (Positioning, Navigation, and Timing) solutions is being studied. This concept opens the possibility to provide high accuracy positioning overcoming the typical drawbacks of RTK (Real-Time Kinematics) or PPP (Precise Point Positioning), such as the need for ground infrastructure or long convergence times. The high velocity dynamics of the low orbits can help to cancel the effect of the ionosphere in the signals to be processed at the user level. Therefore, the introduction of LEO satellites together with the classical MEO GNSS constellations could be a solution to reduce the dependency on dense station networks. The size of the LEO constellations and the design of their orbits are key factors to improve the PPP solution. Moreover, both the accuracy and the convergence time of the PPP solution depend also on the quality of the on-board equipment of the satellite, especially on the quality of the atomic clock in terms of stability and noise, and on the quality of the orbit and clock corrections sent to the PPP users. GMV has decades of experience in both GNSS and LEO precise orbit determination (POD) fields and in high-accuracy GNSS applications for different market domains. With this experience, several analyses have been carried out to assess the achievable performance when introducing the processing of LEO signals for high accuracy positioning solutions, contributing to the overall GNSS community. The objective of this paper is to describe the analysis run by GMV with the use of synthetic data simulating GNSS and LEO signals, showing results and the associated assessment of the achievable performance. Full article