Advances in Space Research最新文献

TEC increment evaluation technique during X class flares using GNSS data 基于GNSS数据的X级耀斑TEC增量评估技术

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.044

V.S. Lobanova, I.A. Ryakhovsky, B.G. Gavrilov, A.I. Sapunova, Y.V. Poklad, V.M. Ermak

The increase in X-ray and ultraviolet irradiance during solar flares leads to a significant increment in the electron concentration in the ionosphere. The use of GNSS receivers allows us to estimate the change in the electron concentration in the ionosphere by estimating the total electron content of the ionosphere (TEC) on the receiver-satellite beam. Some difficulty in estimating this parameter is associated with the dependence of the TEC value on the satellite position in time. To solve this problem, methods for removing this non-linear trend from the measurement data series are used. The main technique for detrending the TEC data is the use of bandpass filtering of the data by averaging them over a certain time interval (the moving average method) or the selection of high-order polynomials that best approximate the general nature of the data change (the polynomial approximation). In this paper, a new technique is proposed for removing the trend from the TEC series for estimating the ionospheric dynamics during solar flares, which uses the averaged TEC data for several days preceding the flare under study. The article presents the results of using this technique based on the experimental data from the Mikhnevo Geophysical Observatory during the X-class flares in September 2017. It is shown that the results of data processing using current and polynomial techniques are in good agreement in the flare front interval, but differ during its decline, which may be due to the need to specify the end time of the flare when approximating the trend with a polynomial. At the same time, variations in solar radiation fluxes in the ultraviolet band have a complex shape during the recovery period, which must be taken into account when removing the trend from the TEC data.

太阳耀斑期间x射线和紫外线辐照度的增加导致电离层中电子浓度的显著增加。GNSS接收机的使用使我们能够通过估计接收机-卫星波束上电离层（TEC）的总电子含量来估计电离层中电子浓度的变化。估计该参数的一些困难与TEC值随卫星时间位置的依赖性有关。为了解决这个问题，使用了从测量数据序列中去除这种非线性趋势的方法。消除TEC数据趋势的主要技术是通过在一定时间间隔内对数据进行平均（移动平均法）或选择最接近数据变化的一般性质的高阶多项式（多项式近似）来使用数据的带通滤波。本文提出了一种利用太阳耀斑发生前数天的平均TEC数据，从TEC序列中去除电离层动态变化趋势的新方法。本文基于2017年9月米赫涅沃地球物理观测站在x级耀斑期间的实验数据，介绍了使用该技术的结果。结果表明，用电流和多项式方法处理的数据结果在耀斑锋面区间内是一致的，但在耀斑锋面下降期间却存在差异，这可能是由于用多项式逼近耀斑趋势时需要指定耀斑结束时间所致。同时，在恢复期间，太阳紫外线波段辐射通量的变化具有复杂的形状，在从TEC数据中去除趋势时必须考虑到这一点。

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引用次数: 0

Modelization of the MiniCaLMa neutron monitor based on Geant4 and Garfield++ 基于Geant4和garfield++的MiniCaLMa中子监测仪建模

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.12.009

Alberto Regadío , Juan José Blanco , J. Ignacio García Tejedor , Carlo Luis Guerrero , Du Toit Strauss

This paper describes the simulation of a portable neutron monitor suited for cosmic ray observation by detecting secondary particles, mainly neutrons, produced in the interaction of cosmic rays and solar energetic particles with the atmosphere. These instruments are known as mini neutron monitors and we focus on one of these detectors called MiniCaLMa from mini Castilla-La Mancha Neutron Monitor which is based on BF₃ for neutron detection. The model was developed using Geant4 to characterize the detector response to neutron beams and Garfield++ to simulate the ion/electron pair avalanches produced by these interactions. Incremental tests have validated the accuracy of the Geant4 model with calibrated measurements from standard NM64 neutron monitors. In addition, the raw pulses generated by the combined Geant4 and Garfield++ simulations show a qualitative alignment with the experimentally measured pulses in the detector. The simulations successfully reproduced the proportional region providing accurate pulse height spectra.

本文描述了一种适用于宇宙射线观测的便携式中子监测仪的模拟，通过探测宇宙射线和太阳高能粒子与大气相互作用中产生的次级粒子，主要是中子。这些仪器被称为微型中子监测器，我们关注其中一个探测器，叫做MiniCaLMa，来自小型Castilla-La Mancha中子监测器，它基于BF3进行中子探测。该模型使用Geant4来表征探测器对中子束的响应，使用Garfield++来模拟这些相互作用产生的离子/电子对雪崩。增量测试通过标准NM64中子监测器的校准测量验证了Geant4模型的准确性。此外，由Geant4和Garfield++联合模拟产生的原始脉冲与探测器中实验测量的脉冲在定性上一致。模拟成功地再现了比例区域，提供了精确的脉冲高度谱。

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引用次数: 0

Preface: Spectroscopy and data in investigation of the active galactic nuclei 前言：研究活动星系核的光谱学和数据

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.12.013

Milan S. Dimitrijević (Guest Editor), Luka Č. Popović (Guest Editor)

引用次数: 0

Self-learning signal classifier for HF coherent scatter radars 高频相干散射雷达自学习信号分类器

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.074

Oleg Berngardt, Ivan Lavygin

The paper presents a method for automatic constructing a classifier for processed data obtained by HF coherent scatter radars. The method is based only on the radar data obtained, the results of automatic modeling of radio wave propagation in the ionosphere, and mathematical criteria for estimating the quality of the models. The final classifier is the model trained on data obtained by 12 radars of the SuperDARN and SECIRA networks over two years for each radar. The model has 2,669 coefficients. For the classification, the model uses both the calculated parameters of radio wave propagation in the model ionosphere and the parameters directly measured by the radar. We calibrated elevation measurements using meteor trail echoes. The analysis revealed 37 optimal classes, with 25 frequently observed. The analysis made it possible to choose 14 classes from them, which are confidently separated in other variants of model training. A preliminary interpretation of 10 of them was carried out. The dynamics of observation of various classes and their dependence on the geographical latitude of radars at different levels of solar and geomagnetic activity were presented, the result aligns with known physical mechanisms. The analysis showed that the most important parameters to identify the classes are the shape of the signal ray tracing trajectory in its second half, the ray traced scattering height and the Doppler velocity measured by the radar.

提出了一种对高频相干散射雷达处理后的数据自动构造分类器的方法。该方法仅基于获得的雷达数据、无线电波在电离层传播的自动模拟结果以及估计模型质量的数学准则。最后的分类器是对superdamn和SECIRA网络的12部雷达在两年多的时间里获得的数据进行训练的模型。该模型有2669个系数。在分类时，该模型既使用了模型电离层中无线电波传播的计算参数，也使用了雷达直接测量的参数。我们用流星轨迹回波校准了海拔高度。分析显示了37个最佳类别，其中25个经常被观察到。分析使得从中选择14个类成为可能，这些类在模型训练的其他变体中被自信地分离开来。对其中10项进行了初步解释。给出了在不同太阳和地磁活动水平下，各类观测动态及其对雷达地理纬度的依赖关系，其结果与已知的物理机制一致。分析表明，信号后半段射线追踪轨迹的形状、射线追踪散射高度和雷达测得的多普勒速度是识别该类的最重要参数。

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引用次数: 0

Prediction of thermospheric CO2 emission using Machine Learning Technique 利用机器学习技术预测热层二氧化碳排放

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.070

Tikemani Bag , Yasunobu Ogawa , V. Sivakumar , Swati Garg

We utilized seventeen (2002–2018) years of CO₂ 15 µm infrared radiative emission (exiting Longwave Radiation, ELR) observations by SABER (Sounding of Atmosphere by using Broadband Emission Radiometry) onboard the TIMED (Thermosphere Ionosphere Mesosphere Energetics and Dynamics) satellite to develop a Machine Learning prediction model. The prediction model, CO₂ML, uses the Random Forest algorithm by considering 150 decision trees with the maximum depth of 30. The inputs are the solar, geomagnetic and atmospheric parameters obtained from SABER and OMNIWeb database. The CO₂ ELR data are divided into training and testing datasets in the ratio of 80:20 those correspond to the period of 2002–2015 and 2015–2018, respectively. The CO₂ML model demonstrates strong correlations with SABER observations, achieving R-value of 0.996 (R = 0.996) for training and 0.968 (R = 0.968) for testing, indicating its predictive performance. In order to further examine its predictability, the CO₂ML is applied to investigate a geomagnetic storm event that occurred during September 7–9, 2017. The CO₂ML shows a very good prediction closely tracking the SABER observation with a relative mean square error (RMSE) of 0.384 mW/m². This performance surpassed the TIEGCM-simulated results which exhibited a higher RMSE of 0.895 mW/m² with significantly underestimated CO₂ ELR. The CO₂ML successfully captures the spatial and temporal variations of CO₂ ELR during both solar active and quiet periods, demonstrating its promise for atmospheric prediction applications.

我们利用TIMED（热层电离层中间层能量学和动力学）卫星上的SABER（利用宽带发射辐射法探测大气）的17年（2002-2018）CO2 15µm红外辐射发射（存在长波辐射，ELR）观测数据来开发机器学习预测模型。预测模型CO2ML使用随机森林算法，考虑150棵决策树，最大深度为30。输入是来自SABER和OMNIWeb数据库的太阳、地磁和大气参数。CO2 ELR数据按80:20的比例分为训练数据集和测试数据集，分别对应2002-2015年和2015-2018年。CO2ML模型与SABER观测值具有较强的相关性，训练模型的R值为0.996 (R = 0.996)，检验模型的R值为0.968 (R = 0.968)，表明其预测性能良好。为了进一步检验其可预测性，应用CO2ML对2017年9月7日至9日发生的地磁风暴事件进行了研究。CO2ML具有非常好的预测效果，与SABER观测结果密切相关，相对均方误差（RMSE）为0.384 mW/m2。这一性能超过了tiegcm模拟结果，后者在显著低估CO2 ELR的情况下显示出0.895 mW/m2的较高RMSE。CO2ML成功地捕获了太阳活动期和太阳静止期CO2 ELR的时空变化，显示了其在大气预测中的应用前景。

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引用次数: 0

Enhancing thermospheric density modeling using bias factor analysis 利用偏倚因子分析增强热层密度模型

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.058

Yao Wu , Junyu Chen , Chusen Lin , Zijie Li , Yaobin Fang , Yu Wu

Accurate thermospheric density modeling is critical for predicting atmospheric drag and satellite orbit evolution. Empirical models often show biases under different solar and geomagnetic conditions. In this study, we developed TT-NRL, a hybrid temporal convolutional network(TCN)-Transformer framework designed to calibrate the NRLMSISE-00 using satellite orbit data. The model is trained on CHAMP accelerometer-derived densities combined with space weather and positional parameters, using the density ratio between observations and model outputs as the target. Evaluations across annual, monthly, and daily scales demonstrate consistent error reductions compared with NRLMSISE-00 during both quiet and storm-time conditions. TT-NRL provides balanced improvements in both short- and long-term scenarios, establishing it as a reliable framework for enhancing empirical thermospheric density models.

准确的热层密度模型是预测大气阻力和卫星轨道演变的关键。经验模型在不同的太阳和地磁条件下往往显示出偏差。在这项研究中，我们开发了TT-NRL，一种混合时间卷积网络(TCN)-变压器框架，旨在使用卫星轨道数据校准NRLMSISE-00。模型以观测值与模型输出的密度比为目标，结合空间天气和位置参数对CHAMP加速度计的密度进行训练。在年度、月度和每日尺度上的评估表明，与NRLMSISE-00相比，在安静和风暴时间条件下，误差都有一致的降低。TT-NRL在短期和长期情景中都提供了平衡的改进，使其成为增强经验热层密度模型的可靠框架。

引用次数: 0

Deep recurrent neural network-based satellite indirect pose tracking with adaptive Huber loss 基于深度递归神经网络的自适应Huber损失卫星间接姿态跟踪

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.021

Zilong Chen , Qianzhi Li , Rui Zhong , Haichao Gui

The relative pose and motion tracking of a satellite is a key technology for autonomous proximity operation missions. Most convolutional neural network (CNN)-based pose estimation methods are evaluated on satellite images with random poses, and thus cannot capture the temporal correlation of inter-frame features when faced with sequential images. To address this problem, this paper presents an innovative keypoint temporal tracking network, which estimates pixel coordinates of a set of pre-defined keypoints from a motion sequence by incorporating the temporal information. It leverages the sequence-modeling capabilities of long short-term memory units to process features extracted by a CNN backbone. Then keypoint sequences are associated with the corresponding 3D keypoints on a priori satellite 3D model to formulate the PnP problem. Subsequently, this paper also proposes an adaptive Huber loss that adaptively updates the switching threshold between mean squared error and mean absolute error based on the prediction residuals of each batch. Compared with original Huber loss, it can achieve a better trade-off between robustness to outliers and estimation accuracy. Finally, extensive simulations on the SPEED and the proposed HEDE sequence datasets validate the effectiveness of the proposed method.

卫星相对姿态和运动跟踪是自主近距离操作任务的关键技术。大多数基于卷积神经网络（CNN）的姿态估计方法都是在具有随机姿态的卫星图像上进行评估，因此在面对序列图像时无法捕捉帧间特征的时间相关性。为了解决这一问题，本文提出了一种创新的关键点时间跟踪网络，该网络通过结合时间信息从运动序列中估计一组预定义关键点的像素坐标。它利用长短期记忆单元的序列建模能力来处理由CNN主干提取的特征。然后将关键点序列与先验卫星三维模型上相应的三维关键点相关联，形成PnP问题。随后，本文还提出了一种基于每批预测残差自适应更新均方误差和平均绝对误差切换阈值的自适应Huber损失算法。与原始的Huber损失相比，它能更好地平衡对离群值的鲁棒性和估计精度。最后，在SPEED和所提出的HEDE序列数据集上进行了大量仿真，验证了所提出方法的有效性。

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引用次数: 0

Real-time estimation of inter-system bias with BDS-3 PPP-B2b by repairing the frequent jumps of satellite clock datum 利用卫星时钟基准面频繁跳变修复BDS-3 PPP-B2b实时估计系统间偏差

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.051

Cancan Wang, Lin Pan

Multi-system combined precise point positioning (PPP) requires the introduction of inter-system bias (ISB) parameters to absorb the difference of receiver code hardware delay and satellite clock datum among different satellite systems. Compared with the strategy estimating multiple receiver clock offset parameters, the strategy estimating ISB parameters can utilize the time-varying characteristics of ISB to enhance the strength of PPP model, which is conducive to PPP processing in complex environment. In the BDS-3 PPP-B2b real-time precise products, the GPS satellite clock datum jumps frequently, preventing the normal implementation of BDS-3/GPS integrated real-time PPP when applying the ISB estimation strategy. In this study, a real-time repair method for the jumps of satellite clock datum is proposed, and the estimation of PPP-B2b ISB is investigated based on this repair method. The results show that the static positioning accuracy of BDS-3/GPS PPP with an ISB parameter is 10–19 % higher than that with two receiver clock parameters in extremely complex environment by taking PPP-B2b products without satellite clock datum jumps for analysis, which proves the advantage of ISB estimation strategy. When adopting the PPP-B2b products with satellite clock datum jumps and the ISB estimation strategy, the positioning performance of BDS-3/GPS PPP is significantly improved after the satellite clock datum jumps are repaired. In the kinematic mode, compared to the strategy estimating two receiver clock offsets and estimating ISB without repairing the clock datum jumps, the proposed method improves the positioning accuracy by 5–22 % and 57–62 %, and shortens the convergence time by 1 % and 27 %. The receiver type and the cross-version upgrade of receiver firmware can affect the magnitude of ISB estimates, while the antenna type and the point release update of receiver firmware version have little effect on ISB estimates. The short-term stability of epoch-wise ISB estimates is 1.161 ns, while the long-term stability of daily ISB estimates is 6.731 ns. The ISB is modeled using a model containing a quadratic function and a 6th-order periodic function, and the single-day modeling accuracy of the ISB can reach 0.169 ns. Meanwhile, the static BDS-3/GPS PPP achieves an accuracy improvement of 3–14 % after the application of the ISB constraint.

多系统组合精确点定位（PPP）需要引入系统间偏差（ISB）参数来吸收不同卫星系统间接收机编码硬件延迟和卫星时钟基准的差异。与估计多个接收机时钟偏移参数的策略相比，估计ISB参数的策略可以利用ISB的时变特性增强PPP模型的强度，有利于复杂环境下的PPP处理。在BDS-3 PPP- b2b实时精密产品中，GPS卫星时钟基准跳变频繁，影响了采用ISB估计策略时BDS-3/GPS一体化实时PPP的正常实施。本文提出了一种实时修复卫星时钟基准跳变的方法，并基于该方法对PPP-B2b ISB估计进行了研究。结果表明，在极端复杂的环境下，采用无卫星时钟基准跳变的PPP- b2b产品进行分析，带ISB参数的BDS-3/GPS PPP静态定位精度比带两个接收机时钟参数的定位精度高10 - 19%，证明了ISB估计策略的优越性。采用带卫星时钟基准点跳变的PPP- b2b产品和ISB估计策略，修复卫星时钟基准点跳变后，BDS-3/GPS PPP定位性能显著提高。在运动模式下，与估计两个接收机时钟偏移和估计ISB而不修复时钟基准跳变的策略相比，该方法的定位精度分别提高了5 ~ 22%和57 ~ 62%，收敛时间分别缩短了1%和27%。接收机类型和接收机固件的跨版本升级会影响ISB估计的大小，而天线类型和接收机固件版本的点发布更新对ISB估计的影响很小。逐时ISB估计的短期稳定性为1.161 ns，而每日ISB估计的长期稳定性为6.731 ns。采用包含二次函数和6阶周期函数的模型对ISB进行建模，单日建模精度可达0.169 ns。同时，采用ISB约束后，静态BDS-3/GPS PPP精度提高了3 ~ 14%。

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引用次数: 0

Multi-parameter GNSS monitoring for expansive soil hazards: a case study from coastal Texas 多参数GNSS监测膨胀土危害：以德克萨斯州沿海地区为例

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.052

Xiongchuan Chen , Shuangcheng Zhang , Yong Fang , Qingtao Zhang , Lidu Zhao , Peng An , Ning Liu , Qi Liu , Ningkang An , Jun Li , Zhilei Ye

Expansive soils present a major challenge to geotechnical engineering, and effective and universally applicable monitoring techniques have become an important scientific problem that needs to be addressed for expansive soil hazard monitoring and prevention. Global navigation satellite system (GNSS) technology, which provides real-time, all-weather three-dimensional localization, has gradually become a common method for monitoring expansive soil hazards. In previous studies, GNSS technology was used mainly to monitor surface deformation information. However, these studies disregarded the ability of the GNSS L-band signal to invert surface environment information around a station. In this paper, a ground-based GNSS remote sensing system that integrates “rainfall, soil moisture, and three-dimensional deformation” is proposed. Continuous observation data from 92 GNSS stations in the coastal area of Texas for the period of 2014–2024 are combined with the soil moisture and rainfall information. The results show that the GNSS-inverted soil moisture exhibits a strong consistency with ERA5 products, with an average correlation coefficient of 0.47. The expansive deformation of expansive soils is affected by multiple types of monitoring information, and the GNSS inversion of expansive soils has an obvious response relationship with multiple surface environmental parameters, which avoids the unreliability of relying on a single type of monitoring information to monitor the stability state of expansive soils and is valuable for popularization.

膨胀土是岩土工程面临的重大挑战，有效且普遍适用的监测技术已成为膨胀土灾害监测与防治需要解决的重要科学问题。全球卫星导航系统（GNSS）技术可提供实时、全天候的三维定位，已逐渐成为膨胀土灾害监测的常用方法。在以往的研究中，GNSS技术主要用于监测地表变形信息。然而，这些研究忽略了GNSS l波段信号反演台站周围地表环境信息的能力。本文提出了一种集“降雨、土壤水分、三维变形”为一体的地面GNSS遥感系统。利用2014-2024年德克萨斯州沿海地区92个GNSS站点的连续观测数据，结合土壤湿度和降雨信息。结果表明，gnss反演的土壤湿度与ERA5产品具有较强的一致性，平均相关系数为0.47。膨胀土的膨胀变形受多种监测信息的影响，而膨胀土的GNSS反演与多种地表环境参数具有明显的响应关系，避免了依赖单一监测信息监测膨胀土稳定状态的不可靠性，具有推广价值。

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引用次数: 0

First study of polarization jet/SAID using onboard ionosonde on Ionosfera-M satellite 首次利用Ionosfera-M卫星上的机载离子探空仪研究偏振射流/SAID

IF 2.8 3区地球科学 Q2 ASTRONOMY & ASTROPHYSICS

Advances in Space Research

Pub Date : 2026-02-01 DOI: 10.1016/j.asr.2025.11.097

A.A. Sinevich , A.A. Chernyshov , S.A. Pulinets , D.V. Chugunin , M.M. Mogilevsky

We present the first-ever investigation of Polarization Jets/Sub-Auroral Ion Drifts (PJ/SAID) using satellite-borne ionosonde data from the Russian Ionosfera-M mission. Prior to this work, no direct observations of PJ/SAID had been made with an onboard ionosonde. To ensure a comprehensive analysis, we integrate simultaneous measurements from ground-based ionosondes, Total Electron Content (TEC) variation maps, and the Swarm satellite. This multi-instrument approach enables a unique, multi-perspective investigation of PJ/SAID, combining observations from both ground and space. PJ/SAID is detected on the onboard ionosonde ionograms as a sharp drop in the critical frequency (foF2) and the local electron plasma frequency, as well as a reduction in frequency and the disappearance of the F-layer trace within the PJ/SAID band, which is confirmed by ground-based ionosondes. This can be explained by the fact that under conditions of low electron density, the probing signal passes through the ionosphere without being reflected. The study also shows a decrease in the upper hybrid resonance frequency at the altitudes of the upper ionospheric F-layer and the penetration of low-frequency broadcast radio signals into this layer within the PJ/SAID band.

我们提出了偏振射流/亚极光离子漂移（PJ/SAID）的首次调查，使用来自俄罗斯Ionosfera-M任务的卫星载电离声探空仪数据。在这项工作之前，没有使用机载离子探空仪对PJ/SAID进行直接观测。为了确保全面的分析，我们整合了地面离子探空仪、总电子含量（TEC）变化图和Swarm卫星的同步测量。这种多仪器方法结合地面和空间观测，可以对PJ/SAID进行独特的、多视角的调查。机载离子探空仪检测到PJ/SAID为临界频率（foF2）和局部电子等离子体频率的急剧下降，以及PJ/SAID波段内频率的降低和f层迹线的消失，地面离子探空仪证实了这一点。这可以用以下事实来解释：在低电子密度的条件下，探测信号穿过电离层而不被反射。研究还表明，在电离层上部f层高度处，上层混合共振频率降低，低频广播无线电信号在PJ/SAID波段内穿透到该层。

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引用次数: 0