Search Results (75)

The growing population of space debris poses significant risks to operational satellites and future space missions, necessitating innovative and efficient tracking solutions. Ground-based radar for space surveillance has been a central area of research since the early Space Age, with recent advancements emphasizing the use of bistatic radar systems that incorporate sensitive radio telescopes as receivers. This approach offers a cost-effective and scalable solution for monitoring space debris. Preliminary observations demonstrated the viability of employing radio telescopes in bistatic configurations for effective debris tracking. This review provides a comprehensive analysis of experiments utilizing radio telescopes as bistatic receivers, highlighting key advancements, challenges, and potential applications in space surveillance systems. By detailing the progress in this field, this study underscores the critical role of bistatic radar systems in mitigating the growing threat of space debris. 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

In an effort to accomplish the real-time acquisition of the laser ranging results of space debris during the daylight and enhance the observation success rate, this paper establishes a joint distribution model of noise and echo signals grounded on the intensity distribution law of the daylight background noise. Through an in-depth analysis of the measurement characteristics of single-photon detectors, a real-time recognition algorithm based on the disparity in statistical distribution is put forward. This algorithm partitions the observation data into intervals of equal length. It then employs the goodness-of-fit test of the geometric distribution to ascertain the data distribution law. Subsequently, it locates the interval in which the echo signal resides by analyzing the contribution degree of the chi-square statistic. The experimental outcomes indicate that under the circumstances of a laser frequency of 400 Hz and a background noise photon rate of 2 × 10⁷ photons per second, the algorithm is capable of achieving real-time recognition of the echo interval for an intensity of 0.09 echo photons per single pulse within 1 s. This breakthrough resolves the critical challenge of daylight echo discrimination in high-noise environments. This method overcomes the constraints of the traditional signal intensity threshold and offers a novel technical approach for the tracking and precise orbit determination of space debris in a low signal-to-noise ratio environment. Full article

Light curve analysis of defunct satellites is critical for characterizing their rotational motion. An accurate understanding of this aspect will benefit active debris removal and on-orbit servicing missions as part of the solution to the space debris issue. In this study, we explored the attitude behavior of inactive GLONASS satellites, specifically a repeating pattern observed in their spin period evolution. We utilized a large amount of data available in the light curve database maintained by the Astronomical Institute of the University of Bern (AIUB). The morphology of the inactive GLONASS light curves typically features four peaks in two pairs and is presumably attributed to the presence of four evenly distributed thermal control flaps or radiators on the satellite bus. The analysis of the periods extracted from the light curves shows that nearly all of the inactive GLONASS satellites are rotating and exhibit a periodic oscillating pattern in their spin period evolution with an increasing or decreasing secular trend. Through modeling and simulation, we found that the periodic pattern is likely a result of canted solar panels that provide an asymmetry in the satellite model and enable a wind wheel or fan-like mechanism to operate. The secular trend is a consequence of differing values of the specular reflection coefficients of the front and back sides of the solar panels. Assuming an empirical model describing the spin period evolution of 18 selected objects, we found significant variations in the average spin period and amplitude of the oscillations, which range from 8.11 s to 469.58 s and 1.10 s to 513.24 s, respectively. However, the average oscillation period remains relatively constant at around 1 year. Notably, the average spin period correlates well with the average amplitude. The empirical model can be used to extrapolate the spin period in the future, assuming that the oscillating pattern is preserved and roughly shows a linear trend. Full article

The high-precision motion state analysis of space targets has important scientific value and application potential in the fields of geodynamics, geodesy, space collision warning and avoidance, and the capture, recovery, and removal of space debris. With the increasing repetition rate of satellite laser ranging systems, the inversion and analysis of space target motion state based on high-precision and high-repetition-rate satellite laser ranging data has become a hot spot in current research. How to filter out noise and retain valid information from the high-repetition-rate, high-precision laser ranging data has become a challenge. The traditional polynomial fitting method has problems with low data accuracy and erroneous deletion of valid data when processing laser ranging data with complex patterns. To address this problem, this paper innovatively designs a new type of spline function and accordingly proposes a laser ranging data preprocessing method that can automatically adapt to the trend of data variation. The method is validated using various characteristic observation data provided by Changchun station (7237), and the results show that the novel spline method is superior to the traditional method in maintaining the integrity of data patterns and significantly improves the data accuracy. After two iterations of denoising, the RMS of the novel spline method is reduced to one-fourth of that before denoising and as low as one-eighteenth of that of the traditional method, and the accuracy is further improved with the increase of the number of iterations. This study provides a practical and reliable novel solution for the preprocessing of laser ranging data with complex patterns. Full article

With the increasing congestion in orbital environments, on-orbit observation has become critical for spacecraft safety. This study investigated the observation performance of space-based inverse synthetic aperture lidar (ISAL) for monitoring on-orbit targets and space debris in geostationary Earth orbit (GEO) and low Earth orbit (LEO). Using STK simulations, the performances under fly-around and fly-by scenarios were evaluated based on three key parameters: minimum imaging time, pulse repetition frequency (PRF), and signal-to-noise ratio (SNR). The results reveal that while the GEO provided a high PRF and SNR for fly-around observations, longer imaging times limited its practical application, making the fly-by mode more suitable. In contrast, the LEO provided stable fly-around observations with lower system requirements, but the fly-by mode suffered from high PRF demands and a low SNR due to the high relative angular velocity of the target. This study further simulated fly-by observations for actual space debris in both the GEO and LEO, validating ISAL’s performance under different conditions. These findings offer valuable insights into the selection of observation modes and the optimization of ISAL’s performance in on-orbit target and debris monitoring, serving as a foundation for future space-based monitoring systems. Full article

Surveys of fragmentations, especially in the early stages of the given event, are fundamental for determining the number of fragments, identifying and cataloging them, and monitoring their future evolution. The development of a ground-based optical survey strategy, i.e., a suitable observation and detection method for the fragments generated by these events, is an important contribution to acquiring data and monitoring these catastrophic phenomena. An optical survey offers an interesting and cost-effective method that supports radar operations in the Low Earth Orbit regime and can monitor higher orbits where radar cannot be used. This paper presents a developed optical survey strategy for multi-observatory observations. The strategy was tested on the fragmentation event of FREGAT R/B CLUSTER 2, a rocket body with a “dummy” payload, fragmented on 8 April 2024 on a Highly Elliptical Orbit. The observational campaign involved different observatory systems, and it represented a key collaboration within the Inter-Agency Space Debris Coordination Committee. The survey started from a simulation of the cloud of fragments and was implemented by the planification and coordination of different observatory systems with different schemes and methods to scan the sky vault. The acquired survey data were analyzed using machine learning methods to identify the unknown objects, i.e., the fragments. The data acquired were compared with the simulated cloud used for the survey, and a correlation of measurements belonging to the same object was performed. Also, the parent body was characterized in its tumbling motion by the light curve acquisition. Full article

To improve the observation efficiency of space debris surveys, a basic sky survey observation strategy was developed, with the aim of observing more space debris based on the Wide Field Optical Telescope Array run by Shandong University. The characteristics of the telescope and dynamic changes in the movement and position of space debris are considered in this strategy. An objective function was designed based on these factors. Using the pixelated sphere method to finely divide the celestial area, applying the summation filtering method, and using a greedy algorithm, the benefit of the objective function can be maximized, thus generating the optimal sky survey observation strategy. Through simulation and observation experiments, we demonstrate that the greedy algorithm observation strategy significantly improves the number of space debris instances and the number of arc segments with respect to the conventional observation strategy. This not only improves the automation level of space debris observation tasks, but also significantly enhances the execution efficiency of telescopes for debris observation. It is very helpful for cataloging space debris and generating collision warnings. Full article

There is an increasing number of spacecrafts in orbit, and the collision impact of high-speed moving targets, such as space debris, can cause fatal damage to these spacecrafts. It has become increasingly important to rapidly and accurately locate high-speed moving targets in space. In this study, we designed a visible-light telephoto camera for observing high-speed moving targets and a laser rangefinder for measuring the precise distance of these targets, and we proposed a method of using fast steering mirror deflection to quickly direct the emitted laser towards such targets and measure the distance. Based on the principle of photographic imaging and the precise distance of targets, a collinear equation and a spatial target location model based on the internal and external orientation elements of the camera and the target distance were established, and the principle of target location and the method for calculating target point coordinates were determined. We analyzed the composition of target point location error and derived an equation for calculating such errors. Based on the actual values of various error components and the error synthesis theory, the accuracy of target location was calculated to be 26.5 m when the target distance is 30 km (the relative velocity is 8 km/s and the velocity component perpendicular to the camera’s optical axis is less than 3.75 km/s). This study provides a theoretical basis and a method for solving the practical needs of quickly locating high-speed moving targets in space and proposes specific measures to improve target location accuracy. Full article

With the increasing number of space debris, the demand for telescopes to observe space debris is also constantly increasing. The telescope observation scheduling problem requires algorithms to schedule telescopes to maximize observation value within the visible time constraints of space debris, especially when dealing with large-scale problems. This paper proposes a practical heuristic algorithm to solve the telescope observation of space debris scheduling problem. In order to accelerate the solving speed of algorithms on large-scale problems, this paper combines the characteristics of the problem and partitions the large-scale problem into multiple sub-problems according to the observation time. In each sub-problem, a coding method based on the priority of the target going into the queue is proposed in combination with the actual observation data, and a decoding method matching the coding method is designed. In the solution process for each sub-problem, an adaptive variable neighborhood search is used to solve the space debris observation plan. When solving all sub-problems is completed, the observation plans obtained on all sub-problems are combined to obtain the observation plan of the original problem. Full article

The use of near-Earth space has grown dramatically during the last decades, resulting in thousands of active and inactive satellites and a huge amount of space debris. To observe and monitor the near-Earth space environment, radar systems play a major role as they can be operated at any time and under any weather conditions. The Tracking and Imaging Radar (TIRA) is one of the largest space observation radars in the world. It consists of a 34$\mathrm{m}$ Cassegrain antenna, a precise tracking radar, and a high-resolution imaging radar. Since the 1990s, TIRA contributes to the field of space domain awareness by tracking and imaging space objects and by monitoring the debris population. Due to new technologies, modern satellites become smaller, and satellite extensions become more compact. Thus, sensitive high-resolution space observation systems are needed to detect, track, and image these space objects. To fulfill these requirements, TIRA is undergoing a major upgrade. The current imaging radar in the Ku band will be replaced by a new radar with improved geometrical and radiometric resolution operating in the Ka band. Due to its wideband fully polarimetric capability, the new imaging radar will increase the analysis and characterization of space objects. In addition, the tracking radar in the L band is also being currently refurbished. Through its novel modular structure and open design, highly flexible radar modes and precise tracking concepts can be efficiently implemented for enhanced space domain awareness. The new TIRA system will mark the start of a new era for space observation with radar in Europe. Full article

Pore-filling hydrates are the main occurrence forms of marine gas hydrates. Pore characteristics are a vital factor affecting the thermodynamic properties of hydrates and their distribution in sediments. Currently, the characterization of the pore system for hydrate-bearing reservoirs are little reported. Therefore, this paper focuses on the Krishna-Godavari Basin, via various methods to characterize the hydrate-bearing sediments in the region. The results showed that X-ray diffraction (XRD) combined with scanning electron microscopy (SEM) and cast thin section (CTS) can better characterize the mineral composition in the reservoir, high-pressure mercury injection (HPMI) focused on the contribution of pore size to permeability, constant-rate mercury injection (CRMI) had the advantage of distinguishing between the pore space and pore throat, and nuclear magnetic resonance cryoporometry (NMRC) technique can not only obtain the pore size distribution of nanopores with a characterization range greater than nitrogen gas adsorption (N₂GA), but also quantitatively describe the trend of fluids in the pore system with temperature. In terms of the pore system, the KG Basin hydrate reservoir develops nanopores, with a relatively dispersed mineral distribution and high content of pyrite. Rich pyrite debris and foraminifera-rich paleontological shells are observed, which leads to the development of intergranular pores and provides more nanopores. The pore throat concentration and connectivity of the reservoir are high, and the permeability of sediments in the same layer varies greatly. The reason for this phenomenon is the significant difference in average pore radius and pore size contribution to pore permeability. This article provides a reference and guidance for exploring the thermodynamic stability of hydrates in sediments and the exploration and development of hydrates by characterizing the pores of hydrate reservoirs. Full article

The Cislunar economy is thriving with innovative space systems and operation techniques to enhance and uplift the traditional approaches significantly. This paper brings about an approach for sustainable small satellite constellations to retain autonomy for long-term missions in the Cislunar space. The methodology presented is to align the hybrid model of the constellation for Earth and Moon as an integral portion of the Cislunar operations. These hybrid constellations can provide a breakthrough in optimally utilizing the Cislunar space to efficiently deploy prominent missions to be operated and avoid conjunction or collisions forming additional debris. Flower and walker constellation patterns have been combined to form a well-defined orientation for these small satellites to operate and deliver the tasks satisfying the mission objectives. The autonomous multi-parametric analysis for each constellation based in Earth and Moon’s environment has been attained with due consideration to local environments. Specifically, the Solar Radiation Pressure (SRP) is a critical constraint in Cislunar operations and is observed during simulations. These are supported by conjunction analysis using the Monte Carlo technique and also the effect of the SRP on the operating small satellites in real-time scenarios. This is followed by the observed conclusions and the way forward in this fiercely competent Cislunar operation. Full article

Space non-cooperative target recognition is crucial for on-orbit servicing. Multi-satellite cooperation has great potential for broadening the observation scope and enhancing identification efficiency. However, there is currently a lack of research on recognition methods tailored for multi-satellite cooperative observation. In this paper, we propose a novel space non-cooperative target recognition method to identify satellites and debris in images from multi-satellite observations. Firstly, we design an image-stitching algorithm to generate space-wide-area images. Secondly, we propose a two-stage multi-target detection model, a lighter CNN model with distance merge threshold (LCNN-DMT). Specifically, in the first stage, we propose a novel foreground extraction model based on a minimum bounding rectangle with the threshold for distance merging (MBRT-D) to address redundant detection box extraction for satellite components. Then, in the second stage, we propose an improved SqueezeNet model by introducing separable convolution and attention mechanisms for target classification. Moreover, due to the absence of a public multi-target detection dataset containing satellites and debris, we construct two space datasets by introducing a randomized data augmentation strategy. Further experiments demonstrate that our method can achieve high-precision image stitching and superior recognition performance. Our LCNN-DMT model outperforms mainstream algorithms in target localization accuracy with only 0.928 M parameters and 0.464 GFLOPs, making it ideal for on-orbit deployment. Full article

The increasing proliferation of space debris, intermittent space incidents, and the rapid emergence of massive LEO satellite constellations pose significant threats to satellites in orbit. Ground-based optical observations play a crucial role in space surveillance and space situational awareness (SSA). The Zhulong telescopic observation network stands as a pivotal resource in the realm of space object tracking and prediction. This publicly available network plays a critical role in furnishing essential data for accurately delineating and forecasting the orbit of space objects in Earth orbit. Comprising a sophisticated array of hardware components including precise telescopes, optical sensors, and image sensors, the Zhulong network synergistically collaborates to achieve unparalleled levels of precision in tracking and observing space objects. Central to the network’s efficacy is its ability to extract positional information, referred to as angular data, from consecutive images. These angular data serve as the cornerstone for precise orbit determination and prediction. In this study, the CPF (Consolidated Prediction Format) orbit serves as the reference standard against which the accuracy of the angular data is evaluated. The findings reveal that the angular data error of the Zhulong network remains consistently below 3 arcseconds, attesting to its remarkable precision. Moreover, through the accumulation of angular data over time, coupled with the utilization of numerical integration and least squares methods, the Zhulong network facilitates highly accurate orbit determination and prediction for space objects. These methodologies leverage the wealth of data collected by the network to extrapolate trajectories with unprecedented accuracy, offering invaluable insights into the behavior and movement of celestial bodies. The results presented herein underscore the immense potential of electric optic telescopes in the realm of space surveillance. By harnessing the capabilities of the Zhulong network, researchers and astronomers can gain deeper insights into the dynamics of space objects, thereby advancing our understanding of the cosmos. Ultimately, the Zhulong telescopic observation network emerges as a pioneering tool in the quest to unravel the mysteries of the universe. Full article