天基激光烧蚀移除空间碎片的轨道测量和数据处理关键技术研究

Orientation information of space debris is required to improve the orbital prediction accuracy for mitigation or elimination of a significant threat to not only human space activities but also operational satellites. Obtaining orientation information is currently achievable by applying photometry, adaptive optics (AO) and satellite laser ranging (SLR) technologies. In this study, a new method is proposed based on an echo laser pulse waveform (ELPW) for the orientation determination of space debris; its feasibility was also investigated by numerical simulations. Unlike the photometry and AO technologies available just under the sun-illumination condition and the SLR technology applicable only for cooperative targets, the ELPW is achievable by using a high power laser regardless of the above measurement constraints. A mathematical model is derived to generate the ELPW, and the beam broadening and spreading due to the atmospheric turbulence is taken into account. The Gaussian decomposition based on a genetic algorithm was employed to the ELPWs in order to analyze the orientation features. It is demonstrated from the numerical simulations that the ELPWs have distinctive shapes characterizing the orientation of space debris and therefore our approach was capable of providing orientation information.

As an important means of contactless manipulation of targets, optical force has significant application prospects in areas such as light sail propulsion and orbital intervention of space debris. Precise measurement of the optical force generated by spatial targets in complex optical fields is crucial for establishing their spatial dynamics model. The torsion balance can be used to measure the optical torque. We use a 5 μm tungsten fiber to build a torsion balance system to measure the extremely weak optical torque less than 1×10-15 Nm, which can help to establish an accurate model of the interaction between objects and optical forces. At the same time, it provides experimental data for the study of spacecraft orbit control and light sail navigation.

Orbital debris poses an escalating threat to space missions and the long-term sustainability of Earth's orbital environment. The literature proposes various approaches for orbital debris remediation, including the use of multiple space-based lasers that collaboratively engage debris targets. While the proof of concept for this laser-based approach has been demonstrated, critical questions remain about its scalability and responsiveness as the debris population continues to expand rapidly. This paper introduces constellation reconfiguration as a system-level strategy to address these limitations. Through coordinated orbital maneuvers, laser-equipped satellites can dynamically adapt their positions to respond to evolving debris distributions and time-critical events. We formalize this concept as the Reconfigurable Laser-to-Debris Engagement Scheduling Problem (R-L2D-ESP), an optimization framework that determines the optimal sequence of constellation reconfigurations and laser engagements to maximize debris remediation capacity, which quantifies the constellation's ability to nudge, deorbit, or perform just-in-time collision avoidance maneuvers on debris objects. To manage the complexity of this combinatorial optimization problem, we employ a receding horizon approach. Our experiments reveal that reconfigurable constellations significantly outperform static ones, achieving greater debris remediation capacity and successfully deorbiting substantially more debris objects. Additionally, our sensitivity analyses identify the key parameters that influence remediation performance the most, providing essential insights for future system design. These findings demonstrate that constellation reconfiguration represents a promising advancement for laser-based debris removal systems, offering the adaptability and scalability necessary to enhance this particular approach to orbital debris remediation.

The significant expansion of the orbital debris population poses a serious threat to the safety and sustainability of space operations. This paper investigates orbital debris remediation through a constellation of collaborative space-based lasers, leveraging the principle of momentum transfer onto debris via laser ablation. A novel delta-v vector analysis framework quantifies the cumulative effects of multiple concurrent laser-to-debris (L2D) engagements by utilizing the vector composition of the imparted delta-v vectors. The paper formulates the Concurrent Location-Scheduling Optimization Problem (CLSP) to optimize the placement of laser platforms and the scheduling of L2D engagements, aiming to maximize debris remediation capacity. Given the computational intractability of the CLSP, a decomposition strategy is employed, yielding two sequential subproblems: (1) determining optimal laser platform locations via the Maximal Covering Location Problem, and (2) scheduling L2D engagements using a novel integer linear programming approach to maximize debris remediation capacity. Computational experiments evaluate the efficacy of the proposed framework across diverse mission scenarios, demonstrating critical constellation functions such as collaborative and controlled nudging, deorbiting, and just-in-time collision avoidance. A sensitivity analysis further explores the impact of varying the number and distribution of laser platforms on debris remediation capacity, offering insights into optimizing the performance of space-based laser constellations.

No abstract available

Growing numbers of high-speed micro-particles in earth’s space threaten both satellite security and long-term space sustainability. While ground-based systems are capable of monitoring bulk debris, they are not efficient at detecting fast-moving, smaller particles due to sensitivity, cost, and real-time limitations. In response, this work suggests a hybrid Artificial Intelligence (AI)-driven system that pairs deep learning with orbital dynamics for the accurate detection and prediction of space debris paths. Our approach leverages real-time data from the Near-Earth Objects (NEO) dataset on Kaggle to train a Convolutional Neural Network (CNN) for accurate detection, as well as micro-debris classification based on real-time data. In contrast with conventional methods, our system complements AI-driven detection with orbital prediction capability based on Keplerian motion modeling and numerical integration methods, facilitating accurate trajectories under realistic environmental conditions. This two-tiered approach increases predictive accuracy without incurring excessive computational cost, making it amenable for implementation on satellite systems or in the cloud. Detection performance testing shows detection rates above 99%, demonstrating substantial improvement in early warning capability and reducing the likelihood of satellite collisions.

Highlights What are the main findings? A statistical distribution-based algorithm is proposed to distinguish weak echo signals from intense daylight background noise, achieving real-time identification of space debris laser ranging data within 1 s. The method successfully detects echo signals with intensities as low as 0.09 photons per pulse under high-noise conditions (background noise rate: 2 × 107 photons/s), surpassing the traditional intensity threshold constraints. What is the implication of the main finding? Enables continuous daylight tracking and precise orbit determination of space debris in low signal-to-noise ratio (SNR) environments, which is critical for spacecraft safety. Leverages statistical distribution disparities instead of signal intensity, offering a universal framework for weak signal extraction in photon-starved regimes. Abstract 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.

No abstract available

In low-Earth orbit, the already existing population of small and medium debris (between 1 cm and several dozens of cm) is a concrete threat to operational satellites. A space-based laser space debris removal (SLDR) system that can remove hazardous debris around selected space assets appears to be a flexible and effective project. To achieve high-precision tracking and emitting, the optical system of the SLDR mission includes a target-detection telescope and emitting telescope, adopting a common light path structure. The optical design results, system performance, tolerance budget, and detailed stray light control design are presented in this paper. The large-aperture off-axis two-mirror beam-narrowing system characteristics are also discussed in terms of stray light control. This paper will present the lateral-displacement (LD) setting, two-stage fore baffle design, black baffle surface selection, and opening direction of the telescope door. The results showed that the stray light elimination reaches a 10-9 order, meeting design requirements.

Accurate knowledge of low Earth orbit (LEO) space debris coordinates is essential for preventing potentially disastrous collisions, safeguarding space assets, and upholding the sustainability of space activities by minimizing the creation of additional debris. However, traditional ground-based equipment faces challenges when observing fast-moving debris within the dynamic LEO environment due to atmospheric interference and a limited field of view. To address these limitations, this research explores the potential of an in-orbit optical space surveillance network as a promising solution. The effectiveness and performance of the system are analyzed through its utilization of optical sensors distributed across multiple spacecraft within the above-the-horizon constellation, specifically designed to continuously monitor the most densely populated altitude band of 700–1,000 km in LEO. In addition to detailing the satellite perturbed equations of motion and the angles-only measurement model, this article highlights the utilization of the Gauss initial orbit determination (IOD) algorithm as a startup to the unscented Kalman filter to precisely estimate the orbital position and velocity of space debris. Simulations are then performed to analyze IOD accuracy, observation opportunities, orbit estimation accuracy, and tracking capability. The results affirm the viability and promise of the proposed system across various conditions.

The overpopulation of the Earth orbital environment due to space debris and deployment of satellite mega-constellations requires advanced Space Situational Awareness capabilities. Space-based space surveillance (SBSS) systems represent a promising solution to complement traditional ground-based tracking systems. This paper investigates an innovative SBSS concept employing large baseline Distributed Satellite Systems (DSS) equipped with optical sensors to improve space object detection and orbit determination. The proposed system may enhance surveillance performance by exploiting sensor spatial diversity for accurate triangulation, thus enabling direct range measurements while ensuring similar illumination conditions. The paper discusses the basic requirements of the proposed concept and presents observability analyses in terms of the observation volume. The potential contribution of a large baseline DSS to improve surveillance performance and orbit determination capabilities is assessed considering synthetic test cases that exploit realistic simulations including detectability constraints.

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.

The orbit measurement in space has several key challenges like range observability issue, where the distance between two spacecraft becomes unobservable due to changes in their relative angles. However, in existing estimation methods have limitation because variations in relative orientation of spacecraft limit the ability to accurately measure the distance between them accurately. The Split and Merge-Deep Neural Network (SAM-DNN) is proposed for angle only orbit measurement based on distance and velocity using multi fusion method. The split and merge method employed with DNN enhanced the measurement with less relative error for relative distance and inclination. Initially, the data about orbit are acquired and preprocessed by min-max normalization technique to improve generalizability of SAM-DNN model. The pre-processed data are then fed to dynamic and line of sight measurement model to evaluate distance and velocity of objects in the orbit based on line of sight. The experimental results of proposed SAM-DNN show better results in orbit measurement which achieved less error rate for relative distance relative distance of x and y are 0.943 and 0.526 when compared to multi source fusion techniques, multilayer perceptron network and other neural networks.

The space-energy driven laser-ablation debris removal technology can remove or detach multiple centimeter-level space debris in a single mission. However, the space-energy driven platform can only rely on its own equipment capabilities to detect and identify space debris. It is necessary to select multiple potentially removable debris targets to improve the removal efficiency. In this paper, target selection for a space-energy driven laser-ablation debris removal system is analyzed based on ant colony optimization. The intersection and interaction periods were given by the optimal driving sequence calculation for multiple debris. Parameters such as the detection range, pulsed energy, repetition frequency of the laser and trajectory of debris have been considered as inputs of the simulation. Target selection and optimal action time have been calculated when a single debris entered the detection range of the laser system. This optimization can significantly improve the overall efficiency and laser energy utilization of the space-based laser platform for the same randomly generated debris group, compared to the mode driven sequentially according to the order of entering the laser action range. The results showed that after being filtered by the ant colony algorithm, the number of removable debris doubled, and the de-orbit altitude increased by 15.9%. The energy utilization rate of the laser removal system has been improved by 74.6%. This optimization algorithm can significantly improve the overall work efficiency and laser energy utilization rate of the space-energy driven system. It can remove more debris or have a larger effective orbit reduction distance value for all debris.

Space debris poses a serious threat to the safety of the spacecraft. Aiming at the expensive and time-consuming problem of long-term accurate perturbation calculation of space debris, several numerical fitting methods are applied to the determination and prediction of space debris orbit. Lagrange polynomial interpolation, cubic spline interpolation, and Chebyshev polynomial fitting methods are used to interpolate and calculate the space debris trajectory function with high accuracy according to the measured amount of space debris. The orbital prediction of space debris is also carried out a period of time. Through a large number of experiments, the fitting effects of three fitting methods under perturbation conditions with different time intervals and different order of harmonic terms are analyzed. The experiments show that the three numerical fitting methods can ensure the fitting accuracy of space debris trajectory and can quickly calculate the position and velocity of space debris at any time.

No abstract available

No abstract available

Due to the growing number of fragmentationrelated debris and the launch of mega constellations of satellites, the characterization of Resident Space Objects has been assuming a growing importance in the context of Space Situational Awareness programs to enable accurate orbit propagations and related functionalities such as collision avoidance. Based on the analysis of light curves, photometric characterization can provide useful information concerning the objects’ surface material, shape, and attitude motion. In this context, this paper proposes an attitude motion classifier of unknown space objects using light curves. In particular, the focus is the combination of data from multiple sensors, either ground or space-based, in order to get a more reliable classification than the one arising from a single photometric measurement. Each light curve is classified using a spectral analysis method based on the Lomb-Scargle Periodogram and the Phase Dispersion Minimization approaches. The classifier’s outputs are then fused first at sensor level and then across multiple sensors to derive a unique classification for the observed space object. The performance of the presented architecture is assessed in a numerical environment able to reproduce synthetic light curves accounting for complex object geometries, and a realistic evolution of orbital and rotational dynamics. A correct classification has been produced for all the considered test cases preliminary proving the effectiveness of the proposed approach.

Space debris poses a growing threat to the safety of man-made operational space-borne systems, demanding reliable detection and tracking solutions to mitigate collision risks. Due to the limited data rate resulting from non-sequential computations, practical radar systems typically exhibit low measurement accuracy, particularly over long distances in space. In this work, we propose a Kalman filter-based approach for accurate range and velocity estimation of space debris using space-based linear frequency modulated (LFM) radars. By enabling sequential processing, the proposed method enhances both range and velocity resolution while maintaining a low sampling rate requirement for analog-to-digital converters (ADCs), making it suitable for real-world deployment. The performance of the proposed method is evaluated through simulations and benchmarked against conventional approaches under low signal-to-noise ratio (SNR) conditions which demonstrate its effectiveness in improving tracking accuracy. Simulation results show that the Kalman filter significantly reduces velocity estimation error, especially under low SNR levels. This confirms its practical advantage in space-based debris monitoring applications.

No abstract available

No abstract available

Abstract In this paper, the results of the orbit determination of two Chinese rocket bodies from low earth orbit (LEO) regime based on the picosecond laser measurements provided by one laser sensor are presented. A new approach was implemented that involved using a set of single laser measurements known as full-rate measurements instead of normal points. The computation strategy was applied using three different scenarios, and several key parameters such as root mean square (RMS), RMS of position (RMSPOS), RMS of velocity (RMSVEL), and alert time were determined. The results obtained indicate that the most optimal solution is to use short orbital arcs that are 24 h long. In this case, the average RMSPOS is approximately 345–530 m, the average RMSVEL is approximately 1 m/s, and the average arc RMS is approximately 3.7–7.0 cm. The determined alert time parameter, which refers to the time during which the laser observation of a given object should be repeated, is on average approximately 19.5 h. If longer orbital arcs, such as 2 days or more, are used, RMSPOS and RMSVEL actually reach the level of single centimeters and single millimeters per second, respectively. However, the arc RMS increases significantly to at least decimeters and even above 1 m in some cases. This suggests that the long arc approach is not a favorable solution. In addition, an interesting discovery has been presented that some Chinese launchers are equipped likely with the laser retroreflectors that can easily reflect the laser beam.

High-precision orbital products of space-based gravitational wave detectors are essential for gravitational wave data accuracy. The TianQin project is a typical geocentric high-orbit space-based gravitational wave detection mission, characterized by a diverse range of available orbit determination (OD) techniques. global navigation satellite system (GNSS) technology is capable of providing continuous observation conditions and serves as the primary space-based OD method for TianQin. However, due to signal attenuation and the performance limitations of onboard equipment, relying solely on GNSS for TianQin OD is unlikely to achieve the precision required for data processing. This article, focusing on TianQin, innovatively proposes the enhancement of TianQin’s GNSS-based OD by leveraging high-precision intersatellite laser links (ISLLs). Building upon GNSS observation data, this study incorporates intersatellite measurement constraints to establish a network-wide joint parameter estimation model. By forming a unified constraint across multiple satellites and solving for each detector’s parameters in an integrated manner, this approach overcomes the limitations of traditional individual detector-by-detector OD, which fails to fully exploit the ultrahigh precision constraints of ISLLs to enhance orbital accuracy. To evaluate the proposed method, we conducted simulation experiments. The results demonstrate that the incorporation of ISLLs significantly enhances both the convergence speed and accuracy. Over a 7-day arc, the proposed ISLL-enhanced method combined with four GNSS signals achieved 3-D position and velocity accuracies of 2.05 m and 0.13 mm/s, respectively. These results, corresponding to improvements of 85% and 83% over four GNSS-only solutions, demonstrate the critical role of ISLLs in overcoming sparse-signal limitations at high Earth orbits.

Satellite laser ranging (SLR) is an important technique that determines geodetic parameters, and its observation processing often calibrates range bias corrections to offset systematic errors. However, the impact of different range bias calibration methods on estimating the BDS-3 satellite orbit and Earth Rotation Parameters (ERP) has not been fully studied. The aim of this study is to explore the impact of employing different SLR range bias corrections on the accuracy of SLR-based BDS-3 satellite orbit and ERP. Eight months of experimental analysis revealed that the station–satellite-pair-dependent range bias correction resulted in the optimal orbit accuracy. Regarding orbit differences relative to precise ephemerides and overlap differences, the 3D root-mean-square (RMS) of satellites manufactured by the China Academy of Space Technology (CAST) are 1.00 and 0.94 m, respectively. The corresponding values of satellites manufactured by the Shanghai Engineering Center for Microsatellites (SECM) are 0.98 and 0.90 m, respectively. The station–satellite-pair-dependent range bias correction performed the best in terms of pole coordinate accuracy. The RMS of the XP and YP differences relative to the International Earth Rotation and Reference Systems Service (IERS) 20 C04 product are 1.32 and 1.41 mas, respectively. The solution using satellite-dependent range bias corrections has the optimal length of day (LOD) accuracy, with a 44.92 μs rms of the LOD difference. However, due to the apparent satellite-related error characteristic reflected in the SLR residual, the station-dependent range bias correction is unsuitable for simultaneously processing the SLR observations of all BDS-3 satellites.

No abstract available

We demonstrate a novel single-shot method to determine the detonation energy of laser-induced plasma and investigate its performance. This approach can be used in cases where there are significant shot-to-shot variations in ablation conditions, such as laser fluctuations, target inhomogeneity, or multiple filamentation with ultrashort pulses. The Sedov blast model is used to fit two time-delayed shadowgrams measured with a double-pulse laser. We find that the reconstruction of detonation parameters is insensitive to the choice of interpulse delay in double-pulse shadowgraphy. In contrast, the initial assumption of expansion dimensionality has a large impact on the reconstructed detonation energy. The method allows for a reduction in the uncertainties of blast wave energy measurements as a diagnostic technique employed in various laser ablation applications.

A recent large low-earth orbit (LEO) constellation program used several small satellites on the order of 104. Even a low failure rate means that dozens of satellites could lose control and become debris. Because they are located in an operational orbit, they pose a serious problem. Therefore, a few active debris removal (ADR) ideas have been proposed, which is to tow and deorbit debris satellites with rescue satellites similar to tugboats for shipwrecks. In these cases, physical contact, such as towing by wire, is a prerequisite. Mechanical coupling between the two satellites Involves risks such as collision between satellites and loss of attitude control at the time of coupling. Since the cooperation between the two satellites is not desirable, mechanical contact is very difficult when the debris has high angular momentum. On the other hand, it is a contactless debris removing idea. to irradiate debris satellites with lasers, and the use of the laser ablation induced impulse, has been proposed.1 In this approach. it is important to accumulate data on how much impulse is generated by the plasma plume produced by laser ablation in a vacuum. A compact and efficient measurement device to measure this impulse has been developed.2 We investigated Impulses generated by a 10ns Q-switched Nd:YAG laser (1064nm) and its second harmonic (SH, 532nm) using a metal as a target for laser irradiation. The results show that the fundamental (1064nm) laser of about 100W can generate enough thrust to de-orbit space debris with comparable mass to a small satellite from 1000km to 500km altitude in a year. SHG can be converted to Impulse more efficiently than 1064nm.2, 3 Meanwhile, research is also being conducted on rendezvous operations with control of the attitude as well as the orbit of the target debris using laser ablation to orbit demonstration in the late 2020s.4 Future improvements in the energy efficiency of laser ablation ADR are desirable and require understanding the physics of thrust generation by ablation. Although the magnitude of the impulse generated relative to the laser pulse width has been estimated semi-quantitatively and empirically,5 the physical elementary processes of ablation are poorly understood. We plan to measure the ablation impulse under various conditions, various ablation materials, laser wavelength of 100nm through several microns, and pulse widths of nano to femto seconds to provide data for theoretical studies. As a first report of this study, we will report the results of impulse measurements generated by a 10ns laser with 1064nm, 532nm, and 355nm on aluminum alloy, copper, and carbon fiber reinforced plastic (CFRP) targets. We will continue to make measurements using lasers at 266nm and other wavelengths.

We demonstrate a novel single-shot approach to determine the detonation energy of laser-induced plasmas. The method employs a double-pulse shadowgraphy scheme coupled with analysis of shock expansion rates using the Sedov blast model.

Laser ablation propulsion and orbit cleaning are developing areas of research. The general aim of laser-based techniques applied to this field is to maximize the momentum transfer produced by a laser shot. This work presents results from ballistic pendulum experiments under vacuum on aluminum, copper, tin, gold, and porous graphite targets. The work has focused on the metrology of the laser experiments to ensure good stability over a wide range of laser parameters (laser intensity ranging from 4 GW/cm2 to 8.7 TW/cm2, pulse duration from 80 ps to 15 ns, and wavelengths of 528 or 1057 nm). The results presented compile data from three experimental campaigns spanning from 2018 to 2021 on two different laser platforms and using different pulse durations, energies, and wavelengths. The study is complemented by the simulation of the momentum from the mono-dimensional Lagrangian code ESTHER. The first part of this work gives a detailed description of the experimental setup used, the ESTHER code, and the treatment of the simulations. The second part focuses on the experimental results. The third part describes the simulation results and provides a comparison with the experimental data. The last part presents possible improvements for future work on the subject.

Based on the on-orbit laser intra-orbit and interorbit link establishment scenarios of a certain constellation satellite, this paper analyzes the error sources affecting the initial laser uncertainty region, establishes an error source model, and through on-orbit star calibration, realizes that after the calibration of 500 km low-orbit satellite, the field of uncertainty(FOU) is about $\mathbf{0. 5} \boldsymbol{\sim} \mathbf{0. 8 m r a d}$. It also analyzes the accuracy of the target satellite orbit extrapolation, which is the main error source. Using the $\mathbf{5}$-hour base point data after orbit determination and orbit measurement for extrapolation, the accuracy is better than 100 meters, and the 10 -hour base point extrapolation accuracy after orbit determination and orbit measurement is about 300 meters. The fastest acquisition time is $\mathbf{1} \boldsymbol{\sim} \mathbf{2}$ seconds. After calibration, the on-orbit pointing uncertainty region is about $\mathbf{0. 6} \boldsymbol{\sim} \mathbf{0. 9 m r a d}$, the fastest acquisition time is about 30 seconds, and cross-network laser communication between different constellations is realized.

A critical requirement to achieve high efficiency of debris laser tracking is to have sufficiently accurate orbit predictions (OP) in both the pointing direction (better than 20 arc seconds) and distance from the tracking station to the debris objects, with the former more important than the latter because of the narrow laser beam. When the two line element (TLE) is used to provide the orbit predictions, the resultant pointing errors are usually on the order of tens to hundreds of arc seconds. In practice, therefore, angular observations of debris objects are first collected using an optical tracking sensor, and then used to guide the laser beam pointing to the objects. The manual guidance may cause interrupts to the laser tracking, and consequently loss of valuable laser tracking data. This paper presents a real-time orbit determination (OD) and prediction method to realize smooth and efficient debris laser tracking. The method uses TLE-computed positions and angles over a short-arc of less than 2 min as observations in an OD process where simplified force models are considered. After the OD convergence, the OP is performed from the last observation epoch to the end of the tracking pass. Simulation and real tracking data processing results show that the pointing prediction errors are usually less than 10″, and the distance errors less than 100 m, therefore, the prediction accuracy is sufficient for the blind laser tracking.

Even a low failure rate means that dozens of satellites could lose control and become debris. Because they are located in an operational orbit, they pose a serious problem. Therefore, a few active debris removal (ADR) ideas have been proposed, which is to tow and de-orbit debris satellites with rescue satellites similar to tugboats for shipwrecks. In these cases, physical contact, such as towing by wire, is a prerequisite. Mechanical coupling between satellites involves risks such as the collision between satellites and loss of attitude control at the time of coupling. Since no cooperation between the two satellites is not desirable, mechanical contact is very difficult when the debris has high angular momentum. On the other hand, the contactless debris removing idea, to irradiate debris satellites with lasers and use of the laser ablation induced impulse, has been proposed. In this approach ti, is important to accumulate data on how much impulse is generated by the plasma plume produced by laser ablation in a vacuum. A compact and efficient measurement device to measure this impulse has been developed. In this study, we investigated impulses generated by a 10ns Q-switched Nd:YAG laser (1064nm) and its second harmonic generation (SHG, 532nm) using a metal as a target for laser irradiation. The results show that the fundamental (1064nm) laser of about 100W can generate enough thrust to deorbit space debris with comparable mass to a small satellite from 1000km to 500km altitude in a year. SHG can be converted to impulse more efficiently than 1064nm. The use of 532nm alone, including the SHG generation efficiency, has less impact on the impulse generation effect than the use of 1064nm fundamental alone, without SHG. It was pointed out that the energy of the Nd:YAG laser effectively uses generation of impulse when the remaining fundamental components that could not be converted to SHG could be used to irradiate to generate ablation. Although the use of SHG is not effective in terms of 1064nm fundamental power including SHG generation efficiency, it is demonstrated that the energy of the Nd:YAG laser can be efficiently utilized by using the remaining fundamental components that could not be converted to SHG.

This work outlines and assesses several methods for the detection of manoeuvres in Low Earth Orbit (LEO) from surveillance radar data. To be able to detect manoeuvres, the main starting assumption is that the object under analysis has an orbit known with a sufficient degree of precision. Based on the precise (a posteriori) orbit and radar data, several manoeuvre detection methods are presented; one is based on unscented Kalman filtering, whereas two others algorithms are based on reachability analysis of the state, which correlates its prediction set with the next track from the radar. The filtering algorithm can be extended for several radar tracks, whereas the reachability-based methods are more precise in detecting manoeuvres. Then, to inherit the best properties of both classes of algorithms, a manoeuvre detection filter that combines both concepts is finally presented. Manoeuvre detection results are presented first for simulated scenarios -- for validation and calibration purposes -- and later for real data. Radar information comes from the Spanish Space Surveillance Radar (S3TSR), with real manoeuvre information and high-quality ephemerides. The results show promise, taking into account that a single surveillance radar is the only source of data, obtaining manoeuvre detection rates of more than 50% and false positive rates of less than 10%.

As the density of spacecraft in Earth's orbit increases, their recognition, pose and trajectory identification becomes crucial for averting potential collisions and executing debris removal operations. However, training models able to identify a spacecraft and its pose presents a significant challenge due to a lack of available image data for model training. This paper puts forth an innovative framework for generating realistic synthetic datasets of Resident Space Object (RSO) imagery. Using the International Space Station (ISS) as a test case, it goes on to combine image regression with image restoration methodologies to estimate pose from blurred images. An analysis of the proposed image recovery and regression techniques was undertaken, providing insights into the performance, potential enhancements and limitations when applied to real imagery of RSOs. The image recovery approach investigated involves first applying image deconvolution using an effective point spread function, followed by detail object extraction with a U-Net. Interestingly, using only U-Net for image reconstruction the best pose performance was attained, reducing the average Mean Squared Error in image recovery by 97.28% and the average angular error by 71.9%. The successful application of U-Net image restoration combined with the Resnet50 regression network for pose estimation of the International Space Station demonstrates the value of a diverse set of evaluation tools for effective solutions to real-world problems such as the analysis of distant objects in Earth's orbit.

For exploration of space, in particular in attempts to find new extra-terrestrial resources, human society has encountered the problem of space pollution with human-made debris, which represents high risks for space missions. This prompted extensive activities for cleaning the space using various techniques, which are briefly overviewed here. But the main focus of this paper is on using lasers for space debris removal. The attention is drawn to laser beam shaping techniques, which are discussed as potential technologies for deorbiting space debris, providing more energetically favorable laser propulsion compared to conventional laser beams.

No abstract available

Space debris is a major concern for the development of human space activities and has a significant impact on space resources. This is a pressing issue that needs to be addressed by countries around the world. High-power picosecond lasers have been found to be effective in enhancing the detection range and accuracy of space targets. This technology can be used for collision warning of orbiting spacecraft, and removal of space debris. In fact, a kHz infrared ranging system for space debris has been successfully established by high-power burst-mode picosecond lasers. This system operates at a wavelength of 1,064 nm, a repetition rate of 1 kHz with 4 pulses in a burst, and an average power of 30 W. It has been able to obtain over 240 effective observation data points of space debris. The system has successfully detected targets at distances exceeding 1,700 km, with a best detection accuracy of 2 cm. Additionally, it has achieved a minimum equivalent radar cross section (1,000 km) of 0.04 m 2 . These results demonstrate the superiority of burst-mode picosecond lasers in the infrared band in terms of detection range. By improving the ranging accuracy to the decimeter level, this technology provides essential references for high-precision debris

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No abstract available

Satellite laser ranging allows to measure distances to satellites equipped with retroreflectors in orbits up to 36000 km. Utilizing a higher powered laser, space debris laser ranging detects diffuse reflections from defunct satellites or rocket bodies up to a distance of 3000 km. So far space debris laser ranging was only possible within a few hours around twilight while it is dark at the satellite laser ranging station and space debris is illuminated by the sun. Here we present space debris laser ranging results during daylight. Space debris objects are visualized against the blue sky background and biases corrected in real-time. The results are a starting point for all space debris laser ranging stations to drastically increase their output in the near future. A network of a few stations worldwide will be able to improve orbital predictions significantly as necessary for removal missions, conjunction warnings, avoidance maneuvers or attitude determination. Space debris laser ranging is a technique to measure distances to defunct satellites or rocket bodies in orbits around Earth which was only possible within a few hours around twilight. Here, the authors show the first space debris laser ranging results during daylight while correcting inaccurate predictions using a real-time target detection software.

No abstract available

No abstract available

Single-photon LiDAR (SPL) offers unprecedented sensitivity and time resolution, which enables satellite laser ranging (SLR) systems to identify space debris from distances spanning thousands of kilometers. However, the existing SPL systems face limitations in distance-trajectory extraction due to the widespread and undifferentiated noise photons. In this letter, we propose a novel velocity-based sparse photon clustering (VBSPC) algorithm, leveraging the velocity correlation of the target’s echo signal photons in the distance-time dimension, by computing and searching the velocity and acceleration of photon distance points between adjacent pulses over a period of time and subsequently clustering photons with the same velocity and acceleration. Our algorithm can extract object trajectories from sparse photon data, even in low signal-to-noise ratio (SNR) conditions. To verify our method, we establish a ground simulation experimental setup for a single-photon ranging LiDAR system. The experimental results show that our algorithm can extract the quadratic track with over 99% accuracy in only tens of milliseconds, with a signal photon-counting rate of 5% at −20-dB SNR. Our method provides an effective approach for detecting and sensing extremely weak signals at the subphoton level in space.

No abstract available

The growth of space debris population smaller than 10 cm in Earth orbit is alarming for the safety of active missions. Observation campaigns fail to target objects of this size, as they are undetectable with optical or radar instruments from ground-based observations. For this reason, modern satellite-based detection strategies are proposed. Implementing simulations and virtual instruments is crucial to evaluate the performance of detection systems equipped on active satellites. Recently, the FGI (Finland), the CSEM (Switzerland) and the ESA/ESTEC (the Netherlands) presented the Coincidental Orbiting Laser Sheet Particle Monitor (COLA). COLA is a simulation developed to exploit the potential of laser sheets and fast detectors to track particles in the mm-cm size range with a population modelled by the software MASTER (developed by ESA). The simulation provides also photometric data, strengthening the developed detection model; an advantage of photometric data is that they allow the use of methods such as light curve inversion, which was initially developed to model asteroids with the LCInvert software. INAOE (Mexico) implemented light curve inversion software similar to the LCInvert and successfully applied it to actual and simulated data. We present the code implementation for curve inversion developed on objects detected by the COLA system. We extend the satellite system from one satellite of a dual laser sheet to a swarm of six satellites. The first main satellite has the laser sheet and a secondary beam that is triggered on by the first detected photon by the sheets. Five passive observers with wide angle cameras measure the target from multiple directions as it passes through the field of view. The observations thus produce a light curve that allowed us to recover the shape and orientation state with the inversion method. We constructed synthetic light curves using random trajectory test particles representing flakes, grains, and needles. The results reached a minimum relative error of 12.38 % for the grain in the inclination of the pole. The azimuth of the pole presented a minimum error of 5.61 % for the flake. Finally, the difference between the simulated curves and the curves obtained after performing the inversion presents a squared error of 5.29×10−2, 2.77×10−2 and 2.38×10−2 for the grain, flake and needle, respectively. In future work, we will seek to optimize the configuration of the satellite swarm and implement a light curve inversion method that considers light scattering from human-made objects.

Space debris is a major threat to the satellite infrastructure. A collision with even small particle, e.g. 1 cm of size, can cause a catastrophic event when the parent body, spacecraft or upper stage, will break up into hundreds of trackable fragments. Space debris research helps to discover, monitor and characterize these objects, identify their origin and support their active removal. Surveys with optical telescopes aim to discover new objects for cataloguing and to increase the accuracy of space debris population models. The follow-up observations are performed to improve their orbits or to investigate their physical characteristics. We will present the space debris population, its orbital and physical characteristics and we will discuss the role which the optical telescopes play in space debris research. We will also discuss the adopted astronomical techniques like astrometry, photometry and spectroscopy used in the space debris domain.

We use a 1030 nm laser with 7 ps pulse duration and average power up to 100 W to ablate pyramid-shape subwavelength structures (SWS) on alumina and sapphire. The SWS give an effective and cryogenically robust anti-reflection coating in the millimeter-wave band. We demonstrate average ablation rate of up to 34 mm$^3$/min and 20 mm$^3$/min for structure heights of 900 $μ$m and 750 $μ$m on alumina and sapphire, respectively. These rates are a factor of 34 and 9 higher than reported previously on similar structures. We propose a model that relates structure height to cumulative laser fluence. The model depends on the absorption length $δ$, which is assumed to depend on peak fluence, and on the threshold fluence $φ_{th}$. Using a best-fit procedure we find an average $δ= 630$ nm and 650 nm, and $φ_{th} = 2.0^{+0.5}_{-0.5}$ J/cm$^2$ and $2.3^{+0.1}_{-0.1}$ J/cm$^2$ for alumina and sapphire, respectively, for peak fluence values between 30 and 70 J/cm$^{2}$. With the best fit values, the model and data values for cumulative fluence agree to within 10%. Given inputs for $δ$ and $φ_{th}$ the model is used to predict average ablation rates as a function of SWS height and average laser power.

Measurements are reported of the target neutralization current, the target charge, and the tangential component of the magnetic field generated as a result of laser-target interaction by pulses with the energy in the range of 45 mJ to 92 mJ on target and the pulse duration from 39 fs to 1000 fs. The experiment was performed at the Eclipse facility in CELIA, Bordeaux. The aim of the experiment was to extend investigations performed for the thick (mm scale) targets to the case of thin (micrometer thickness) targets in a way that would allow for a straightforward comparison of the results. We found that thin foil targets tend to generate 20 to 50 percent higher neutralization current and the target charge than the thick targets. The measurement of the tangential component of the magnetic field had shown that the initial spike is dominated by the 1 ns pulse consistent with the 1 ns pulse of the neutralization current, but there are some differences between targets of different type on sub-ns scale, which is an effect going beyond a simple picture of the target acting as an antenna. The sub-ns structure appears to be reproducible to surprising degree. We found that there is in general a linear correlation between the maximum value of the magnetic field and the maximum neutralization current, which supports the target-antenna picture, except for pulses hundreds of fs long.

The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to (I) represent general orbital debris and SSA domain knowledge, (II) structure, and standardize where needed, orbital data and terminology, and (III) foster semantic interoperability and data-sharing. In doing so I hope to (IV) contribute to solving the orbital debris problem, improving peaceful global SSA, and ensuring safe space travel for future generations.

Binary feature descriptors have been widely used in various visual measurement tasks, particularly those with limited computing resources and storage capacities. Existing binary descriptors may not perform well for long-term visual measurement tasks due to their sensitivity to illumination variations. It can be observed that when image illumination changes dramatically, the relative relationship among local patches mostly remains intact. Based on the observation, consequently, this study presents an illumination-insensitive binary (IIB) descriptor by leveraging the local inter-patch invariance exhibited in multiple spatial granularities to deal with unfavorable illumination variations. By taking advantage of integral images for local patch feature computation, a highly efficient IIB descriptor is achieved. It can encode scalable features in multiple spatial granularities, thus facilitating a computationally efficient hierarchical matching from coarse to fine. Moreover, the IIB descriptor can also apply to other types of image data, such as depth maps and semantic segmentation results, when available in some applications. Numerical experiments on both natural and synthetic datasets reveal that the proposed IIB descriptor outperforms state-of-the-art binary descriptors and some testing float descriptors. The proposed IIB descriptor has also been successfully employed in a demo system for long-term visual localization. The code of the IIB descriptor will be publicly available.

The exponential rise in small-satellites and CubeSats in Low Earth Orbit (LEO) poses important challenges for future space traffic management. At altitudes of 600 km and lower, aerodynamic drag accelerates de-orbiting of satellites. However, placement of satellites at higher altitudes required for constellations pose important challenges. The satellites will require on-board propulsion to lower their orbits to 600 km and let aerodynamic drag take-over. In this work we analyze solutions for de-orbiting satellites at altitudes of up to 3000 km. We consider a modular robotic de-orbit device that has stowed volume of a regular CubeSat. The de-orbit device would be externally directed towards a dead satellite or placed on one by an external satellite servicing system. Our solutions are intended to be simple, high-reliability devices that operate in a passive manner, requiring no active electronics or utilize external beamed power in the form of radio frequency, microwave or laser to operate. Utilizing this approach, it is possible for an external, even ground based system to direct the de-orbit of a spacecraft. The role of an external system to direct the de-orbit is important to avoid accidental collisions. Some form of propulsion is needed to lower the orbit of the dead satellite or orbital debris. We considered green (non-toxic) propulsion methods including solar radiation pressure, solar-thermal propulsion using water steam, solar-electrolysis propulsion using water and use of electrodynamic tethers. Based on this trade-study we identify multiple solutions that can be used to de-orbit a spacecraft or orbital debris.

This paper presents a novel methodology for improving the performance of machine learning based space traffic management tasks through the use of a pre-trained orbit model. Taking inspiration from BERT-like self-supervised language models in the field of natural language processing, we introduce ORBERT, and demonstrate the ability of such a model to leverage large quantities of readily available orbit data to learn meaningful representations that can be used to aid in downstream tasks. As a proof of concept of this approach we consider the task of all vs. all conjunction screening, phrased here as a machine learning time series classification task. We show that leveraging unlabelled orbit data leads to improved performance, and that the proposed approach can be particularly beneficial for tasks where the availability of labelled data is limited.

The surface degradation of satellites in Low Earth Orbit (LEO) is affected by Atomic Oxygen (AO) and varies depending on the spacecraft orbital parameters. Atomic oxygen initiates several chemical and physical reactions with materials and produces erosion and self-disintegration of the debris at high energy. This paper discusses Avancee-1 Mission, LiDAR-based space debris removal using Optical Neural Networks (ONN) to optimize debris detection and mission accuracy. The SaDoD Method is a Stimulated Atomic Disintegration of Orbital Debris, which in this case has been achieved using LiDAR technology and Optical Neural Networks. We propose Optical Neural Network algorithms with a high ability of image detection and classification. The results show that orbital debris has a higher chance of disintegration when the laser beam is coming from Geostationary Orbit (GEO) satellites and in the presence of high solar activities. This paper proposes a LiDAR-based space debris removal method depending on the variation of atomic oxygen erosion with orbital parameters and solar energy levels. The results obtained show that orbital debris undergoes the most intense degradation at low altitudes and higher temperatures. The satellites in GEO use Optical Neural Network algorithms for object detection before sending the laser beams to achieve self-disintegration. The SaDoD Method can be implemented with other techniques, but especially for the Avancee-1 Mission, the SaDoD was implemented with LiDAR technologies and Optical Neural Network algorithms.

An alternative, new laser link acquisition scheme for the triangular constellation of spacecraft (SCs) in deep space in the detection of gravitational waves is considered. In place of a wide field CCD camera in the initial stage of laser link acquisition adopted in the conventional scheme, an extended Kalman filter based on precision orbit determination is incorporated in the point ahead angle mechanism (PAAM) to steer the laser beam in such a way to narrow the uncertainty cone and at the same time avoids the heating problem generated by the CCD camera.A quadrant photodetector (QPD) based on the Differential Power Sensing (DPS) technique, which offers a higher dynamic range than differential wavefront sensing (DWS), is employed as the readout of the laser beam spot. The conventional two stages (coarse acquisition and fine acquisition) are integrated into a single control loop. The payload structure of the ATP control loop is simplified and numerical simulations, based on a colored measurement noise model that closely mimics the prospective on-orbit conditions, demonstrate that the AEKF significantly reduces the initial uncertainty region by predicting the point ahead angle (PAA) even when the worst case scenario in SC position (navigation) error is considered.

A study of damage and ablation of silicon induced by two individual femtosecond laser pulses of different wavelengths, 1030 and 515 nm, is performed to address the physical mechanisms of dual-wavelength ablation and reveal possibilities for increasing the ablation efficiency. The produced ablation craters and damaged areas are analyzed as a function of time separation between the pulses and are compared with monochromatic pulses of the same total energy. Particular attention is given to low-fluence irradiation regimes when the energy densities in each pulse are below the ablation threshold and thus no shielding of the subsequent pulse by the ablation products occurs. The sequence order of pulses is demonstrated to be essential in bi-color ablation with higher material removal rates when a shorter-wavelength pulse arrives first at the surface. At long delays of 30-100 ps, the dual-wavelength ablation is found to be particularly strong with the formation of deep smooth craters. This is explained by the expansion of a hot liquid layer produced by the first pulse with a drastic decrease in the surface reflectivity at this timescale. The results provide insight into the processes of dual-wavelength laser ablation offering a better control of the energy deposition into material.

A comparative experimental study of pulsed laser ablation in vacuum of two binary semiconductors, zinc oxide and indium phosphide, has been performed using IR-and visible laser pulses with particular attention to cluster generation. Neutral and cationic Zn\_n O\_m and In\_n P\_m particles of various stoichiometry have been produced and investigated by time-of-flight mass spectrometry. At ZnO ablation, large cationic (n>9) and all neutral clusters are mainly stoichiometric in the ablation plume. In contrast, indium phosphide clusters are strongly indium-rich with In\_4 P being a magic cluster. Analysis of the plume composition upon laser exposure has revealed congruent vaporization of ZnO and a disproportionate loss of phosphorus by the irradiated InP surface. Plume expansion conditions under ZnO ablation are shown to be favourable for stoichiometric cluster formation. A delayed vaporization of phosphorus under InP ablation has been observed that results in generation of off-stoichiometric clusters.

Pulsed laser ablation propulsion has the potential to revolutionize space exploration by eliminating the requirement of a spacecraft to carry its propellant and power source as the high-power laser is situated off-board. More experimentation needs to be done to optimize this propulsion system and understand the mechanisms of thrust generation. There are many methods used to calculate the impulse imparted in pulsed laser ablation experiments. In this paper, key performance parameters are derived for some of the impulse measurement methods used in ablation propulsion experiments. Regimes discussed include the torsional pendulum system, simple pendulum system, and solid and liquid microspheres.

The effect of the laser ray incidence angle on the mass ablation rate and ablation pressure of planar inertial confinement fusion (ICF) targets is explored using an idealized model. Polar direct drive (PDD) on the National Ignition Facility (NIF) requires the repointing of its 192 beams clustered within 50 degrees of the poles to minimize the imparted polar varying payload kinetic energy of the target. Due to this repointing, non-normal incidence angles of the beam centerlines are encountered in any PDD design. The formulation of a PDD scheme that minimizes non-uniformity is a significant challenge that requires an understanding of the induced differences in ablation including those of incidence angle. In this work, a modified version of the textbook model of laser ablation [Manheimer et al. Phys. Fluids 25, 1644 (1982)] is used to demonstrate that the mass ablation rate and ablation pressure scale with the 4/3 and 2/3 power of the cosine of the laser ray incidence angle for the planar case during the beginning portion of the laser ablation. This result is considered with an idealized 1-D two segment planar model using rays at different incidence angles for each segment. Within the model, the segments cannot have equal mass and velocity simultaneously without tailoring the ray's time-dependent intensity for each segment. However, with the correct segment-to-segment time-independent ray intensities, equal velocity and dynamic pressure can be achieved approximately without tailoring. Additionally, an analytic prediction for the conduction zone width as a function of incidence angle is provided. It is predicted that this width increases with incidence angle, resulting in a decrease in laser imprint, an effect which has been previously observed in experiments. These results, when generalized to spherical geometry, may provide insight into the implosion dynamics encountered in PDD.

We provide measurements of ablation of four post-transition and transition metals (aluminum, copper, nickel and tungsten) irradiated by single 800 nm laser pulses, in ultrashort regime from 100 fs pulse duration down to 15 fs covering a temporal range little explored yet. For each metal and pulse duration tested, we measure its ablation characteristics (depth and diameter) as a function of incident energy allowing us to determine its laser-induced ablation threshold and ablation rate in single-shot regime. For all metals studied, we observe constant ablation threshold fluence as a function of pulse duration extending this scaling law to pulse duration of few-optical-cycles. We also provide evidence of the interest of adjusting the incident fluence to maximize the energy specific ablation depth but also of the absence of any peculiar advantage related to the use of extremely short pulse duration for ablation purposes. Those informative and detailed ablation data have been obtained in single pulse regime and in air ambiance. They can serve as rewarding feedback for further establishing smart strategy for femtosecond laser micromachining and laser damage handling of metallic and metal-based components as well as for enhancing accuracy of modeling of femtosecond laser interaction with metals in ultrashort regime.

The classification of space debris and active satellites is crucial for maintaining space situational awareness and preventing collisions. This study presents a machine learning approach that utilizes two-line element (TLE) data to distinguish between satellites and debris based on key orbital parameters, including eccentricity, inclination, mean motion, right ascension of the ascending node (RAAN), and semi-major axis. Two modelsa feedforward neural network (FNN) and a random forest classifier- were developed and evaluated for their classification performance. The TLE-derived parameters were preprocessed to address data inconsistencies, with the feature importance analysis revealing the inclination and the semi-major axis as dominant discriminators. The Random Forest model utilized an ensemble of decision trees with Gini impurity criteria, while the FNN employed a three-layer architecture with ReLU activation and dropout regularization. The random forest classifier achieved superior accuracy (92.4%) compared to the FNN (87.1%), demonstrating robustness to noisy TLE data and non-linear feature relationships. Both models significantly outperformed traditional clustering-based taxonomic methods, particularly in handling edge cases such as debris with satellite-like orbits. This data-driven approach provides a scalable alternative to resource-intensive optical or radar-based classification systems. Future work will integrate the temporal evolution of orbital parameters to address decaying orbits and the detection of maneuvers.