Advances in Space Research最新文献_第4页

Time-series InSAR monitoring and evolution predictive analysis of filling-area subsidence in Yan’an New District 延安新区充填区沉降时序InSAR监测及演化预测分析

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-23 DOI: 10.1016/j.asr.2026.01.069

Kangyi Chen , Bo Zhang , Hang Jiang , Jichao Lv , Anmengyun Liu , Yanan Jiang , Rui Zhang

Since the completion of large-scale filling in 2015, Yan’an New District (YAND) has experienced notable ground deformation during rapid urban development. To reveal the spatial–temporal evolution of subsidence, this study integrates SBAS-InSAR monitoring with a newly developed Extended Long Short-Term Memory (xLSTM) prediction model. Using 153 Sentinel-1A images from 2020 to 2025, SBAS-InSAR provided continuous five-year ground deformation results, indicating maximum cumulative uplift of 57.7 mm and maximum cumulative subsidence of 141.1 mm, with peak subsidence rates reaching 26.29 mm/a. Three major subsidence belts were identified, mainly distributed in filled construction areas, with seasonally accelerated subsidence occurring in summer and autumn. The core innovation of this study lies in application in ground deformation of the xLSTM model, which effectively overcomes the temporal lag and limited long-term dependency issues inherent in conventional LSTM models, thereby improving subsidence trend prediction accuracy and responsiveness to evolving deformation patterns. The integration of historical deformation signals and xLSTM prediction results suggests that ground deformation in YAND is gradually entering a stabilization stage. This research provides a robust and scalable framework for high-precision urban subsidence monitoring and early-warning, offering valuable references for land development and risk management in rapidly expanding loess-region cities.

延安新区自2015年完成大规模填埋以来，在城市快速发展过程中，地表变形显著。为了揭示沉降的时空演变，本研究将SBAS-InSAR监测与新开发的扩展长短期记忆（xLSTM）预测模型相结合。利用153幅2020 - 2025年的Sentinel-1A影像，SBAS-InSAR提供了连续5年的地面变形结果，最大累计隆升57.7 mm，最大累计沉降141.1 mm，最大沉降速率达到26.29 mm/a。确定了3个主要沉降带，主要分布在填筑区，季节性加速沉降主要发生在夏季和秋季。本研究的核心创新点在于将xLSTM模型应用于地面变形，有效克服了传统LSTM模型固有的时间滞后和有限的长期依赖问题，从而提高了沉降趋势预测的精度和对变形模式演变的响应能力。综合历史变形信号和xLSTM预测结果表明，YAND地区地面变形正逐渐进入稳定阶段。该研究为高精度城市沉降监测预警提供了稳健、可扩展的框架，为快速扩张的黄土地区城市的土地开发和风险管理提供了有价值的参考。

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引用次数: 0

Research on high-resolution PM2.5 concentration estimation methods based on transfer learning 基于迁移学习的高分辨率PM2.5浓度估算方法研究

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-21 DOI: 10.1016/j.asr.2026.01.052

Meiling Xing, Bo Li, Wenhao Zhang, Guohong Li, Xiufeng Yang, Qiyue Liu, Qichao Zhao

High-resolution PM_2.5 data are pivotal for cities aiming to implement detailed pollution control strategies. However, current high-resolution PM_2.5 estimation methods often suffer from limited model generalization and suboptimal transferability. In this study, we employed Gaofen-1/6 satellite top-of-atmosphere (TOA) reflectance, coupled with meteorological, population, elevation, and NDVI data, to construct datasets for spatial, temporal, and payload transfers. By incorporating a Deep Belief Network (DBN) model and a fine-tuning-based transfer learning approach, three distinct transfer learning (TL) models were developed. Initially, a DBN model was pretrained using the source domain dataset. Subsequently, the backpropagation (BP) layer of this pretrained model was fine-tuned using the target domain dataset. The results showed that the pretrained DBN model achieved an accuracy of R² = 0.82 and an RMSE 18.35 μg/m³. The performance metrics for the spatial transfer learning model (TL-S), temporal transfer learning model (TL-T), and payload transfer learning model (TL-P) were R² values of 0.78, 0.73, and 0.69, respectively. Notably, these transfer learning models consistently outperformed two other model types: DBN models directly trained on target domain data and pretrained models trained on the source domain dataset. This novel transfer learning method offers a comprehensive validation of transfer efficacy across spatial, temporal, and payload domains. Compared with prior research, our method demonstrates enhanced model generalization and superior spatial resolution. Moreover, at a 100 m resolution, the generated PM_2.5 data offers a more detailed depiction of urban pollution dynamics than public products such as CHAP and LGHAP. Overall, our findings underscore the reliability of the proposed method, positioning it as a valuable benchmark for cross-domain PM_2.5 concentration monitoring.

高分辨率PM2.5数据对于旨在实施详细污染控制策略的城市至关重要。然而，目前的高分辨率PM2.5估算方法往往存在模型泛化有限和可移植性欠佳的问题。本文利用高分1/6卫星大气顶（TOA）反射率，结合气象、人口、高程和NDVI数据，构建时空和有效载荷转移数据集。结合深度信念网络（DBN）模型和基于微调的迁移学习方法，开发了三种不同的迁移学习（TL）模型。首先，使用源域数据集对DBN模型进行预训练。随后，使用目标域数据集对该预训练模型的反向传播（BP）层进行微调。结果表明，预训练DBN模型的准确率为R2 = 0.82， RMSE为18.35 μg/m3。空间迁移学习模型（TL-S）、时间迁移学习模型（TL-T）和有效负载迁移学习模型（TL-P）的绩效指标R2分别为0.78、0.73和0.69。值得注意的是，这些迁移学习模型始终优于其他两种模型类型：直接在目标领域数据上训练的DBN模型和在源领域数据集上训练的预训练模型。这种新颖的迁移学习方法提供了跨空间、时间和有效载荷域的迁移有效性的综合验证。与已有研究相比，该方法具有更强的模型泛化能力和更高的空间分辨率。此外，在100米分辨率下，生成的PM2.5数据提供了比公共产品（如CHAP和LGHAP）更详细的城市污染动态描述。总体而言，我们的研究结果强调了所提出方法的可靠性，将其定位为跨域PM2.5浓度监测的有价值基准。

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引用次数: 0

Space capacity-based metric to rank in orbit collision risk 以空间容量为基础的指标对轨道碰撞风险进行排名

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-28 DOI: 10.1016/j.asr.2026.01.077

Andrea Muciaccia , Francesca Letizia , Mirko Trisolini , Lorenzo Giudici , Stijn Lemmens , Juan Luis Gonzalo , Camilla Colombo

Space capacity is a developing concept, with new models to describe and quantify it emerging in recent years. These models aim to define a sustainable threshold for the space environment, a limit which ensures the continued safety of future launches and satellite operations. They also seek to link this threshold to the impact of both new and existing objects in orbit, effectively assigning each object a share of the total capacity, or the portion it consumes. This definition should be internationally recognised and adopted, serving as the foundation for launch guidelines, debris mitigation strategies, and, more broadly, global Space Traffic Management.

Within this work, the concept of space capacity refers to the capacity consumed by a population, examining how this consumption changes over time. The capacity model is applied to assess the level of risk posed by potential orbital fragmentation. The model compares the difference in space capacity consumption between a scenario with fragmentation and one without, in order to determine whether such an event has a significant impact on overall consumption. This approach provides more insights than just counting the number of objects or fragmentation events.

空间容量是一个发展中的概念，近年来出现了描述和量化空间容量的新模型。这些模型旨在为空间环境确定一个可持续的阈值，这个阈值可以确保未来发射和卫星运行的持续安全。它们还设法将这一阈值与轨道上的新物体和现有物体的影响联系起来，有效地为每个物体分配总容量的一部分，或其消耗的部分。这一定义应得到国际承认和采用，作为发射准则、碎片缓减战略以及更广泛的全球空间交通管理的基础。在这项工作中，空间容量的概念是指人口消耗的容量，研究这种消耗如何随时间变化。利用容量模型对轨道破碎的潜在风险进行了评估。该模型比较有碎片的场景和没有碎片的场景在空间容量消耗方面的差异，以确定此类事件是否对总体消耗产生重大影响。这种方法比仅仅计算对象或碎片事件的数量提供了更多的见解。

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引用次数: 0

From site to region: Performance evaluation of remote sensing-derived GPP products across China 从站点到区域：中国遥感衍生GPP产品的性能评价

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-16 DOI: 10.1016/j.asr.2026.01.038

Yongwei Cao , Zhanghua Xu , Yuanyao Yang , Chaofei Zhang , Na Qin

Gross Primary Productivity (GPP), a critical metric quantifying the total carbon dioxide assimilated by vegetation through photosynthesis, plays a pivotal role in terrestrial ecosystem carbon cycle studies. However, accurately estimating GPP at large scales remains subject to significant uncertainties. This study evaluates four widely used remote sensing-based GPP products (rEC-LUE, MODIS, VPM, GOSIF) across China using eddy covariance data from 66 flux towers. Methodologies include Getis-Ord Gi* hotspot analysis, Sen's slope estimation, Reduced Major Axis (RMA) regression, and partial correlation analysis to assess their spatiotemporal consistency and climatic response patterns. The results indicated that: (1) At the national scale, VPM exhibited the best performance (R² = 0.74). Ecosystem-level evaluations revealed that VPM achieved the highest accuracy for grassland (R² = 0.78) and cropland (R² = 0.87), while GOSIF performed best for forest (R² = 0.78). All four products performed well for the wetland (R² > 0.72). (2) At the site scale, GOSIF showed better agreement with eddy covariance data for most forest and grassland sites, whereas VPM excelled for cropland sites. All products exhibited limited capability in reproducing the interannual variability of site-level GPP. (3) VPM and GOSIF maintained high spatiotemporal consistency across diverse scales and hydrothermal conditions. (4) All products consistently identified precipitation as the dominant driver of GPP variations in northeastern China and the northern Tibetan Plateau. This study can enhance our understanding of vegetation carbon sequestration dynamics in China and provide theoretical support for the development of environmental policies.

总初级生产力（Gross Primary Productivity， GPP）是衡量植被光合作用吸收二氧化碳总量的重要指标，在陆地生态系统碳循环研究中具有重要作用。然而，在大尺度上准确估计GPP仍然存在很大的不确定性。本文利用66个通量塔的涡动相关数据，对中国四种广泛使用的遥感GPP产品（rEC-LUE、MODIS、VPM、GOSIF）进行了评估。方法包括Getis-Ord Gi*热点分析、Sen's斜率估计、RMA回归和偏相关分析，以评估它们的时空一致性和气候响应模式。结果表明：(1)在国家尺度上，VPM表现最佳（R2 = 0.74）。生态系统水平评价结果显示，VPM在草地（R2 = 0.78）和农田（R2 = 0.87）上的精度最高，而GOSIF在森林（R2 = 0.78）上的精度最高。这四种产品在湿地中均表现良好（R2 > 0.72）。(2)在立地尺度上，GOSIF与涡旋相关方差的一致性较好，而VPM在农田尺度上表现较好。所有产品在重现样地水平GPP的年际变化方面表现出有限的能力。(3)在不同尺度和热液条件下，VPM和GOSIF保持了较高的时空一致性。(4)所有产品一致认为降水是中国东北和青藏高原北部地区GPP变化的主导驱动力。该研究可以加深我们对中国植被固碳动态的认识，并为环境政策的制定提供理论支持。

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引用次数: 0

Complexity and scaling descriptors as diagnostic predictors of heliophysical indices across solar-cycle timescales 复杂性和标度描述符作为太阳周期时间尺度上太阳物理指数的诊断预测因子

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-02-10 DOI: 10.1016/j.asr.2026.02.010

D. Sierra-Porta , Maximiliano Canedo Verdugo , Daniel David Herrera Acevedo

Heliophysical variability emerges from a coupled, multiscale system in which changes in the solar atmosphere and heliospheric plasma translate into measurable signatures in widely used activity indices. Operational space-weather workflows often summarize this variability through amplitudes and a small set of bulk solar-wind covariates, yet important dynamical information may also reside in the evolving morphology of the signals. We examine whether shape descriptors computed from heliophysical time series provide information beyond classical amplitude summaries and standard bulk solar-wind covariates. Using daily OMNIWeb-era records spanning 1964–2025, we compute ten sliding-window descriptors under a past-only convention, designed to capture complementary aspects of temporal morphology such as irregularity, roughness, and long-range dependence. The descriptor set combines entropy measures, fractal-dimension estimators, the Hurst exponent, and Lempel–Ziv (LZ) complexity, yielding a compact representation of time-series structure that is not reducible to amplitude alone. The window length is treated as a methodological hyperparameter and selected through a target-specific sensitivity analysis that jointly favors competitive out-of-sample RMSE and stable permutation-importance rankings across neighboring windows.

Two complementary learners, gradient boosting and a multilayer perceptron, are used as diagnostic probes to quantify permutation-based feature relevance under chronological splitting and training-only preprocessing. Across three targets (F10.7, Sunspot Number, and Dst), shape descriptors consistently rank among the most informative predictors, often matching or exceeding the relevance of standard solar-wind inputs. The most robust signals arise from LZ complexity and a compact subset of entropy/fractal measures, whose windowed trajectories track solar-cycle phases with characteristic lead–lag behaviour. Correlation analyses on both levels and standardised first differences expose redundancy within descriptor families and reduce spurious associations driven by shared nonstationarity, motivating a family-level interpretation of relevance rather than causal attribution. Overall, the results indicate that heliophysical time-series morphology encodes dynamical information complementary to amplitude- and bulk-plasma descriptions, suggesting compact, instrument-light features for augmenting future space-weather modelling pipelines.

太阳物理变率产生于一个耦合的多尺度系统，在这个系统中，太阳大气和太阳层等离子体的变化转化为广泛使用的活动指数中可测量的特征。业务空间天气工作流程通常通过振幅和一小组大块太阳风协变量来总结这种可变性，但重要的动力学信息也可能存在于信号的演变形态中。我们研究了从太阳物理时间序列计算的形状描述符是否提供了经典振幅摘要和标准大块太阳风协变量之外的信息。使用从1964年到2025年的omniweb时代的日常记录，我们根据仅限过去的惯例计算了10个滑动窗口描述符，旨在捕捉时间形态的互补方面，如不规则性、粗糙度和长期依赖性。描述符集结合了熵测度、分形维估计量、Hurst指数和Lempel-Ziv （LZ）复杂度，产生了一个紧凑的时间序列结构表示，它不能仅用于幅度。窗口长度被视为方法上的超参数，并通过目标特异性敏感性分析来选择，该分析有利于竞争性样本外RMSE和相邻窗口间稳定的排列重要性排名。两个互补的学习器，梯度增强和多层感知器，被用作诊断探针来量化在时间分裂和仅训练预处理下基于排列的特征相关性。在三个目标（F10.7，太阳黑子数和Dst）中，形状描述符始终是最具信息量的预测因子之一，通常匹配或超过标准太阳风输入的相关性。最强大的信号来自LZ复杂性和熵/分形测量的紧凑子集，其窗口轨迹跟踪具有特征超前滞后行为的太阳周期阶段。对两个层次和标准化第一差异的相关分析揭示了描述符家族中的冗余，并减少了由共享非平稳性驱动的虚假关联，从而激发了家族层面的相关性解释，而不是因果归因。总体而言，结果表明，太阳物理时间序列形态学编码的动态信息与振幅和体积等离子体描述相补充，表明紧凑、仪器轻便的特征可以增强未来的空间天气建模管道。

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引用次数: 0

Qualification of affordable open-source analog and digital Sun sensors for CubeSats 可负担的开源立方体卫星模拟和数字太阳传感器的鉴定

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-29 DOI: 10.1016/j.asr.2026.01.083

Marius Anger , Bruce Clayhills , Nemanja Jovanovic , Anton Fetzer , Petri Niemelä , Christoffer Kauppinen , Jaan Praks

This paper presents the qualification of affordable, open-source analog (PSS) and digital Sun sensors (DSS) for CubeSats, which aim to provide cost-effective and accessible attitude determination solutions for small satellite missions. The study evaluates the performance, reliability, and suitability of these sensors in space-like conditions, addressing key factors such as accuracy, thermal stability, and radiation tolerance. Experimental results demonstrate that the PSS can achieve better than 5° precision over a field of view of 100° while maintaining low costs and power consumption. The DSS shows a precision better than 0.5° over a field of view of 36° using a photolithographically patterned optical aperture acting as a pinhole. The research highlights the potential of these sensors to democratize access to space technology, supporting academic and commercial CubeSat missions with accessible and effective attitude determination solutions.

本文介绍了用于立方体卫星的可负担的、开源的模拟（PSS）和数字太阳传感器（DSS）的资格，旨在为小卫星任务提供具有成本效益和可访问的姿态确定解决方案。该研究评估了这些传感器在类空间条件下的性能、可靠性和适用性，解决了精度、热稳定性和辐射耐受性等关键因素。实验结果表明，在100°视场范围内，PSS可以达到5°以上的精度，同时保持较低的成本和功耗。在36°视场范围内，使用光刻图像化光学孔径作为针孔，DSS显示精度优于0.5°。该研究强调了这些传感器在实现空间技术民主化方面的潜力，通过可访问和有效的姿态确定解决方案支持学术和商业立方体卫星任务。

引用次数: 0

Occurrence characteristics and East-West African differences of plasma bubbles during solar cycle 24 from GPS observations 基于GPS观测的第24太阳周期等离子体气泡的出现特征及东西非洲差异

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-23 DOI: 10.1016/j.asr.2026.01.062

George Ochieng Ondede , Daniel Okoh , Paul Baki , Joseph Olwendo , Adero Awuor

This study presents the first long-term, data-consistent comparison of equatorial plasma bubble (EPB) occurrence over East and West Africa during Solar Cycle 24, using GNSS-derived rate of TEC index (ROTI) from four stations located within ±5° of the dip equator. ROTI-based detection was applied to nine years of observations (2013–2021), enabling assessment of longitudinal differences in EPB occurrence, seasonal patterns, and solar-cycle modulation. Results show a persistent and significant West-East asymmetry. During high solar activity years (2013–2015), EPB occurrence in West Africa was 53.1% at CGGN and 37.8% at DAKR, compared to 35.0% at ADIS in East Africa, indicating that the West African sector experienced approximately 30% higher EPB occurrence, on the average, than the East African sector. Under moderate solar activity (2016, 2017, 2021), West African stations continued to record substantially higher occurrence rates (36.5% and 24.4%) than East African stations (3.6% and 2.5%), exceeding them by about an order of magnitude. During solar minimum (2018–2020), EPB activity was strongly suppressed at all stations but remained relatively more frequent in West Africa. Seasonal analysis shows consistent equinox-centered peaks, with ROTI maxima occurring predominantly during the March and September equinoxes. The results quantitatively demonstrate that the West African dip-equatorial region provides a more favorable electrodynamic environment for EPB development throughout the solar cycle, offering new empirical constraints for longitudinally dependent ionospheric modeling and space-weather forecasting over Africa.

本研究首次对太阳活动周期24期间东非和西非赤道等离子体气泡（EPB）的发生进行了长期、数据一致的比较，使用gnss导出的TEC指数（ROTI）率，这些数据来自位于赤道倾角±5°范围内的四个站点。基于roti的检测应用于9年的观测（2013-2021），能够评估EPB发生、季节模式和太阳周期调制的纵向差异。结果显示持续且显著的西-东不对称。在太阳活动高的年份（2013-2015），西非在CGGN和DAKR的EPB发生率分别为53.1%和37.8%，而东非在ADIS的EPB发生率为35.0%，表明西非地区的EPB发生率平均比东非地区高约30%。在中度太阳活动（2016年、2017年和2021年）下，西非站的发生率（36.5%和24.4%）继续显著高于东非站（3.6%和2.5%），超过它们约一个数量级。在太阳活动极小期（2018-2020），EPB活动在所有站都受到强烈抑制，但在西非仍然相对频繁。季节分析显示，以春分为中心的峰值是一致的，ROTI最大值主要出现在3月和9月春分。结果表明，在整个太阳周期中，西非低赤道地区为EPB的发展提供了更有利的电动力环境，为纵向依赖的电离层模拟和非洲空间天气预报提供了新的经验约束。

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引用次数: 0

STRF-GAN: Research on short-term rainfall forecasting method based on GAN model STRF-GAN：基于GAN模型的短期降雨预报方法研究

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-21 DOI: 10.1016/j.asr.2026.01.057

Xingwang Zhao , Shiguo Deng , Jian Chen , Guanzheng Zhao , Chao Liu , Qiang Niu , Yi Chang , Chao Chen

In order to enhance the accuracy of rainfall forecasting, we analysed the variation characteristics of precipitable water vapor (PWV), temperature (T), pressure (P), dew point temperature (DPT) and relative humidity (RH) during the rainfall process. Then, a short-term rainfall forecast model based on the generative adversarial network (STRF-GAN) was proposed by using the time series data of multiple meteorological parameters. Based on the meteorological data at Beijing (BJFS), Changchun (CHAN), Hong Kong (HKSL), Lhasa (LHAZ), Urumqi (URUM), and Wuhan (WUH2) from 2021 to 2022, we analysed the variation trends and correlations among multiple meteorological parameters, as well as the rainfall forecasting performance of proposed model. The results show that the meteorological parameters have obvious changes before and after the rainfall, and there is a certain correlation between the parameters. Compared with traditional threshold method, gated recurrent unit (GRU), temporal convolutional network (TCN) and convolutional neural network (CNN), the STRF-GAN model has a better accuracy and reliability in rainfall forecasting, with an accuracy, precision, and recall values of better than 94%, 85% and 84%, respectively. Therefore, the STRF-GAN model can effectively capture the variation characteristics of meteorological parameters before and after rainfall, and has a better rainfall forecasting performance.

为了提高降水预报的准确性，分析了降水过程中可降水量（PWV）、温度(T)、压力(P)、露点温度（DPT）和相对湿度（RH）的变化特征。然后，利用多气象参数的时间序列数据，提出了一种基于生成对抗网络（STRF-GAN）的短期降雨预报模型。利用北京（BJFS）、长春（CHAN）、香港（HKSL）、拉萨（LHAZ）、乌鲁木齐（URUM）和武汉（WUH2） 2021 - 2022年的气象资料，分析了多个气象参数的变化趋势和相关性，以及所建模型的降水预报性能。结果表明：降雨前后气象参数变化明显，参数之间存在一定的相关性；与传统的阈值方法、门控循环单元（GRU）、时间卷积网络（TCN）和卷积神经网络（CNN）相比，STRF-GAN模型在降雨预报中具有更好的准确性和可靠性，其准确度、精密度和召回率分别优于94%、85%和84%。因此，STRF-GAN模型能有效捕捉降雨前后气象参数的变化特征，具有较好的降雨预报性能。

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引用次数: 0

Space object classification based on non-conservative force 基于非保守力的空间物体分类

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-02-02 DOI: 10.1016/j.asr.2026.01.080

Zhen Li , Yunlong Deng , Chuang Shi , Qikai Guo , Zhenghang He

The increasingly crowded space environment necessitates enhanced Space Situational Awareness (SSA) capabilities. In the SSA system, the essential task is to classify space objects such as operational satellites and defunct debris for various purposes.Traditional approaches often rely on single observational data like light curve, radar cross section, or optical image. However, orbital parameters, which are updated frequently and cover a much larger population of resident space objects, provide a complementary and information-rich data source. In this study, we explore a novel approach for space object classification based on orbital parameters. We first derive the Non-Conservative Force (NCF) accelerations from the orbital parameters and then extract a set of features from the NCF time series. These features are subsequently used to train several conventional classification algorithm, including support vector machine, k-nearest neighbors, and decision tree. The accuracy of the NCF accelerations is validated using accelerometer measurements from the GRACE-FO C satellite. Our experimental results demonstrate that decision tree achieves an accuracy of 87.51% in distinguishing different categories of space objects based on combinations of RCS size and object type. This indicates that the proposed approach has significant potential for improving classification in SSA systems.

日益拥挤的空间环境需要增强空间态势感知（SSA）能力。在SSA系统中，基本任务是对空间物体进行分类，例如用于各种目的的运行卫星和废弃碎片。传统的方法通常依赖于单一的观测数据，如光曲线、雷达横截面或光学图像。然而，轨道参数经常更新，覆盖更多的驻留空间物体，提供了一个补充和信息丰富的数据源。在本研究中，我们探索了一种基于轨道参数的空间目标分类新方法。首先从轨道参数推导出非保守力加速度，然后从NCF时间序列中提取出一组特征。这些特征随后用于训练几种传统的分类算法，包括支持向量机、k近邻和决策树。利用GRACE-FO C卫星的加速度计测量结果验证了NCF加速度的准确性。实验结果表明，基于RCS大小和目标类型组合的决策树识别不同类别空间目标的准确率达到87.51%。这表明所提出的方法在改进SSA系统的分类方面具有很大的潜力。

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引用次数: 0

Characterization of BDS-3 PPP-B2b ephemeris errors from integrity perspective 基于完整性的BDS-3 PPP-B2b星历误差表征

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-03-15 Epub Date: 2026-01-12 DOI: 10.1016/j.asr.2026.01.023

Zhixi Nie , Zihan Wang , Zhenjie Wang , Ying Xu

Integrity monitoring is crucial for safety critical applications such as the precise navigation and control of unmanned aerial vehicle (UAV), autonomous driving, and unmanned surface vehicle (USV). Although the precision point positioning service via the BDS-3 B2b signal (PPP-B2b) has been widely evaluated in terms of ephemeris accuracy and positioning performance, a systematic integrity assessment of PPP-B2b ephemeris remains absent. To address this gap, this study conducts a comprehensive integrity characterization of PPP-B2b ephemeris errors spanning from November 11, 2023 to February 28, 2025. PPP-B2b orbit and clock errors are calculated through comparison with precise ephemeris provided by the Center for Orbit Determination in Europe (CODE). Then the orbit and clock errors are combined to obtain signal-in-space (SIS) user range errors (UREs). Faulty behaviors including satellite faults and constellation faults are explored, and the probabilities of the two types of faults are carefully counted. In addition, a conservative Gaussian bounding for nominal SIS UREs of each satellite is obtained using the two-step bounding algorithm. The results show the fault probability is 3.7 × 10^–4 for GPS satellites and 1.8 × 10^–4 for BDS-3 satellites. At the constellation level, the fault probability is 8.6 × 10^–8 for GPS and 2.7 × 10^–7 for BDS-3. The bounding results of the nominal errors reveal that GPS corrections exhibit a standard deviation range of 0.107–0.382 m, with a mean value of 0.204 m, whereas BDS-3 corrections show a tighter range of 0.069–0.181 m and a lower mean value of 0.117 m.

完整性监测对于安全关键应用至关重要，例如无人机（UAV）、自动驾驶和无人水面车辆（USV）的精确导航和控制。虽然北斗三号B2b信号的精密点定位服务（PPP-B2b）在星历精度和定位性能方面得到了广泛的评价，但对PPP-B2b星历的系统完整性评估仍然缺乏。为了解决这一差距，本研究对2023年11月11日至2025年2月28日期间PPP-B2b星历误差进行了全面的完整性表征。通过与欧洲定轨中心（CODE）提供的精确星历进行比较，计算了PPP-B2b的轨道和时钟误差。然后将轨道误差和时钟误差相结合，得到空间信号用户距离误差。探讨了卫星故障和星座故障的故障行为，并对两类故障的概率进行了细致的计算。此外，利用两步边界算法得到了各卫星标称SIS边界的保守高斯边界。结果表明，GPS卫星和BDS-3卫星的故障概率分别为3.7 × 10-4和1.8 × 10-4。在星座级别，GPS故障概率为8.6 × 10-8， BDS-3故障概率为2.7 × 10-7。标定误差的边界结果表明，GPS校正的标准差范围为0.107 ~ 0.382 m，均值为0.204 m； BDS-3校正的标准差范围为0.069 ~ 0.181 m，均值较低，为0.117 m。

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