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HAN Jinsheng, YUAN Jing, WANG Qiao, LIU Qinqin, YIN Hanke, LIU Haijun, ZHAO Shufan, SHEN Xvhui, WANG Yali. Fast and Robust Automatic Extraction Method for the Lightning Whistler Scattering Coefficient of the Zhangheng Satellite (in Chinese). Chinese Journal of Space Science, 2025, 45(4): 1-16 doi: 10.11728/cjss2025.04.2023-0127
Citation: HAN Jinsheng, YUAN Jing, WANG Qiao, LIU Qinqin, YIN Hanke, LIU Haijun, ZHAO Shufan, SHEN Xvhui, WANG Yali. Fast and Robust Automatic Extraction Method for the Lightning Whistler Scattering Coefficient of the Zhangheng Satellite (in Chinese). Chinese Journal of Space Science, 2025, 45(4): 1-16 doi: 10.11728/cjss2025.04.2023-0127

Fast and Robust Automatic Extraction Method for the Lightning Whistler Scattering Coefficient of the Zhangheng Satellite

doi: 10.11728/cjss2025.04.2023-0127 cstr: 32142.14.cjss.2023-0127
  • Received Date: 2023-11-13
  • Rev Recd Date: 2024-07-08
  • Available Online: 2024-08-15
  • The daily production data of the Zhangheng satellite can reach up to 20 GB, rendering manual methods inadequate for handling such massive data demands. This paper proposes a rapid and robust Lightning Whistle Scattering Coefficient Automatic Extraction Method (LWSC-AEM): Firstly, detailed data from the Search Coil Magnetometer (SCM) of the Zhangheng satellite is extracted using a sliding window of 0.8 seconds, which is then transformed into time-frequency plots and audio files. Secondly, a YOLOv5 neural network is employed to automatically locate LW in the time-frequency plots and output their time-frequency position information. Subsequently, the corresponding audio data containing Lightning Whistlers is extracted based on this time-frequency position information from the files, and zero-padded to form audio segments of 0.8 seconds. Finally, the Mel Frequency Cepstral Coefficients (MFCCs) of the audio segments are extracted and fed into a Gate Recurrent Unit (GRU) improved with a multi-head attention mechanism to automatically extract the LW scattering coefficient. Applying this method to the data from the VLF band of the SCM payload of the Zhangheng satellite in February 2020 yields the following results: the average absolute error and average absolute percentage error are 0.453 and 0.176 respectively. Compared to the method by Ref.[1], the average absolute error is reduced by 1.079, a decrease of 70%, and the average absolute percentage error is reduced by 0.148, a decrease of 46%. The average processing time per data segment is 0.074 seconds, which is a reduction of 0.826 seconds, or 92%, compared to the method by Ref.[1] , which processed each data segment on average. The automatic extraction method for lightning whistler wave scattering coefficients proposed in this paper can quickly and accurately extract these coefficients.

     

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  • [1]
    CHEN Y P, NI B B, GU X D, et al. First observations of low latitude whistlers using WHU ELF/VLF receiver system[J]. Science China Technological Sciences, 2017, 60(1): 166-174 doi: 10.1007/s11431-016-6103-5
    [2]
    HORNE R B, GLAUERT S A, MEREDITH N P, et al. Space weather impacts on satellites and forecasting the Earth's electron radiation belts with SPACECAST[J]. Space Weather, 2013, 11(4): 169-186 doi: 10.1002/swe.20023
    [3]
    PARROT M, PINÇON J L, SHKLYAR D. Short-fractional hop whistler rate observed by the low-altitude satellite DEMETER at the end of the solar cycle 23[J]. Journal of Geophysical Research: Space Physics, 2019, 124(5): 3522-3531 doi: 10.1029/2018JA026176
    [4]
    KISHORE A, DEO A, KUMAR S. Upper atmospheric remote sensing using ELF–VLF lightning generated tweek and whistler sferics[J]. The South Pacific Journal of Natural and Applied sciences, 2016, 34(1): 12-20 doi: 10.1071/SP16002
    [5]
    CLILVERD M A, NUNN D, LEV-TOV S J, et al. Determining the size of lightning-induced electron precipitation patches[J]. Journal of Geophysical Research: Space Physics, 2002, 107(A8): SIA 10-1-SIA 10-11
    [6]
    OIKE Y, KASAHARA Y, GOTO Y. Spatial distribution and temporal variations of occurrence frequency of lightning whistlers observed by VLF/WBA onboard Akebono[J]. Radio Science, 2014, 49(9): 753-764 doi: 10.1002/2014RS005523
    [7]
    SINGH A K, VERMA U P, BHARGAWA A. Remote sensing of Mid/Upper atmosphere using ELF/VLF waves[J]. Global Journal of Science Frontier Research: A Physics and Space Science, 2018, 18(10): 10-21
    [8]
    BAYUPATI I P A, KASAHARA Y, GOTO Y. Study of dispersion of lightning whistlers observed by Akebono satellite in the earth's plasmasphere[J]. IEICE Transactions on Communications, 2012, E95. B(11): 3472-3479
    [9]
    CARPENTER D L, ANDERSON R R. An ISEE/whistler model of equatorial electron density in the magnetosphere[J]. Journal of Geophysical Research: Space Physics, 1992, 97(A2): 1097-1108 doi: 10.1029/91JA01548
    [10]
    REN Y, DAI L, LI W, et al. Whistler waves driven by field-aligned streaming electrons in the near-Earth magnetotail reconnection[J]. Geophysical Research Letters, 2019, 46(10): 5045-5054 doi: 10.1029/2019GL083283
    [11]
    REN Y, DAI L, WANG C, et al. Statistical characteristics in the spectrum of whistler waves near the diffusion region of dayside magnetopause reconnection[J]. Geophysical Research Letters, 2021, 48(1): e2020GL090816 doi: 10.1029/2020GL090816
    [12]
    周怀北, 肖佐, 孙传礼. 根据哨声频谱反演云—地闪电参数[J]. 电波科学学报, 1989(1): 1-7 doi: 10.13443/j.cjors.1989.01.001

    ZHOU Huaibei, XIAO Zuo, SUN Chuanli. A study of cloud-earth lightning parameters by using whistler spectrum[J]. Chinese Journal of Radio Science, 1989(1): 1-7 doi: 10.13443/j.cjors.1989.01.001
    [13]
    何友文. 哨声“源”的分析[J]. 空间科学学报, 1981, 1(2): 143-152 doi: 10.11728/cjss1981.02.143

    HE Youwen. An analysis of whistler sources[J]. Chinese Journal of Space Science, 1981, 1(2): 143-152 doi: 10.11728/cjss1981.02.143
    [14]
    ARTEMYEV A V, LAPSHIN N V, SIMONOV S A. Prospects of predicting the number of geese on spring migration stopover sites in Karelia[J]. The Herald of Game Management, 2014, 11(2): 249-255
    [15]
    胡云鹏, 泽仁志玛, 黄建平, 等. 张衡一号卫星记录的空间电磁波传播特征分析方法及算法实现[J]. 地球物理学报, 2020, 63(5): 1751-1765 doi: 10.6038/cjg2020N0405

    HU Yunpeng, ZHIMA Zeren, HUANG Jianping, et al. Algorithms and implementation of wave vector analysis tool for the electromagnetic waves recorded by the CSES satellite[J]. Chinese Journal of Geophysics, 2020, 63(5): 1751-1765 doi: 10.6038/cjg2020N0405
    [16]
    HELLIWELL R A. Whistlers and Related Ionospheric Phenomena[M]. Stanford: Stanford University Press, 1965
    [17]
    Stanford VLF Group. Automated detection of whistlers for the TARANIS spacecraft overview of the project[EB/OL]. 2009
    [18]
    DHARMA K S, BAYUPATI I P A, BUANA P W. Automatic lightning whistler detection using connected component labeling method[J]. Journal of Theoretical and Applied Information Technology, 2014, 66(2): 638-645
    [19]
    KONAN O J E Y, MISHRA A K, LOTZ S. Machine learning techniques to detect and characterise whistler radio waves[OL]. arXiv preprint arXiv: 2002.01244v1, 2020
    [20]
    YUAN Jing, WANG Qiao, ZHANG Xuemin, et al. Advances in the automatic detection algorithms for lightning whistlers recorded by electromagnetic satellite data[J]. Chinese Journal of Geophysics, 2021, 64(5): 1471-1495. DOI: 10.6038/cjg2021O0263 (袁静, 王桥, 张学民, 等. 基于电磁卫星的闪电哨声波智能检测算法的研究进展[J]. 地球物理学报, 2021, 64(5): 1471-1495)
    [21]
    YUAN Jing, WANG Qiao, YANG Dehe, et al. Automatic recognition algorithm of lightning whistlers observed by the Search Coil Magnetometer onboard the Zhangheng-1 Satellite[J]. Chinese Journal of Geophysics, 2021, 64(11): 3905-3924. DOI: 10.6038/cjg2021O0164 (袁静, 王桥, 杨德贺, 等. 张衡一号感应磁力仪数据闪电哨声波自动识别[J]. 地球物理学报, 2021, 64(11): 3905-3924)
    [22]
    YUAN Jing, WANG Zijie, ZHIMA Zeren, et al. Automatic recognition algorithm of the lightning whistler waves by using speech processing technology[J]. Chinese Journal of Geophysics, 2022, 65(3): 882-897. DOI: 10.6038/cjg2022P0365 (袁静, 王子杰, 泽仁志玛, 等. 基于智能语音技术的闪电哨声波自动识别[J]. 地球物理学报, 2022, 65(3): 882-897)
    [23]
    ECKERSLEY T L. Musical atmospherics[J]. Nature, 1935, 135(3403): 104-105 doi: 10.1038/135104a0
    [24]
    代牮, 赵旭, 李连鹏, 等. 基于改进YOLOV5的复杂背景红外弱小目标检测算法[J]. 红外技术, 2022, 44(5): 504-512

    DAI Jian, ZHAO Xu, LI Lianpeng, et al. Improved YOLOV5-based infrared dim-small target detection under complex background[J]. Infrared Technology, 2022, 44(5): 504-512
    [25]
    何雨, 田军委, 张震, 等. YOLOV5目标检测的轻量化研究[J]. 计算机工程与应用, 2023, 59(1): 92-99

    HE Yu, TIAN Junwei, ZHANG Zhen, et al. Lightweight research of YOLOV5 target detection[J]. Computer Engineering and Applications, 2023, 59(1): 92-99
    [26]
    SHAO Yanhua, ZHANG Duo, CHU Hongyu, et al. A review of YOLO object detection based on deep learning[J]. Journal of Electronics :Times New Roman;">& Information Technology, 2022, 44(10): 3697-3708. DOI: 10.11999/JEIT210790 (邵延华, 张铎, 楚红雨, 等. 基于深度学习的YOLO目标检测综述[J]. 电子与信息学报, 2022, 44(10): 3697-3708)
    [27]
    庞聪, 江勇, 廖成旺, 等. 基于MFCC样本熵和灰狼算法优化支持向量机的天然地震与人工爆破自动识别[J]. 地震工程学报, 2022, 44(5): 1169-1175

    PANG Cong, JIANG Yong, LIAO Chengwang, et al. Automatic recognition of natural earthquakes and artificial blasting based on the sample entropy of the Mel frequency cepstrum coefficient and support vector machine optimized by gray wolf optimization[J]. China Earthquake Engineering Journal, 2022, 44(5): 1169-1175
    [28]
    袁正午, 肖旺辉. 改进的混合MFCC语音识别算法研究[J]. 计算机工程与应用, 2009, 45(33): 108-110

    YUAN Zhengwu, XIAO Wanghui. Improved speech recognition algorithm based on MFCC feature[J]. Computer Engineering and Applications, 2009, 45(33): 108-110
    [29]
    谭祥勇, 胡天英, 刘锋. Huber损失下线性模型的序列相关检验[J]. 重庆理工大学学报(自然科学), 2023, 37(8): 342-347

    TAN Xiangyong, HU Tianying, LIU Feng. Serial correlation test for linear models under Huber loss[J]. Journal of Chongqing University of Technology (Natural Science), 2023, 37(8): 342-347
    [30]
    AHMAD U, KASAHARA Y, MATSUDA S, et al. Automatic detection of lightning whistlers observed by the plasma wave experiment onboard the Arase satellite using the OpenCV library[J]. Remote Sensing, 2019, 11(15): 1785 doi: 10.3390/rs11151785
    [31]
    CHEN Y P, YANG G B, NI B B, et al. Development of ground-based ELF/VLF receiver system in Wuhan and its first results[J]. Advances in Space Research, 2016, 57(9): 1871-1880. doi: 10.1016/j.asr.2016.01.023
    [32]
    CHRISTIAN H J, BLAKESLEE R J, BOCCIPPIO D J, et al. Global frequency and distribution of lightning as observed from space by the Optical Transient Detector[J]. Journal of Geophysical Research: Atmospheres, 2003, 108(D1): ACL 4-1-ACL 4-15
    [33]
    DOWDEN B L, ALLCOCK G M. Determination of nose frequency of non-nose whistlers[J]. Journal of Atmospheric and Terrestrial Physics, 1971, 33(7): 1125-1129 doi: 10.1016/0021-9169(71)90133-4
    [34]
    FISER J, CHUM J, DIENDORFER G, et al. Whistler intensities above thunderstorms[J]. Annales Geophysicae, 2010, 28(1): 37-46 doi: 10.5194/angeo-28-37-2010
    [35]
    GURNETT D A, KURTH W S, CAIRNS I H, et al. Whistlers in Neptune's magnetosphere: evidence of atmospheric lightning[J]. Journal of Geophysical Research: Space Physics, 1990, 95(A12): 20967-20976 doi: 10.1029/JA095iA12p20967
    [36]
    LICHTENBERGER J, FERENCZ C, BODNÁR L, et al. Automatic whistler detector and analyzer system: automatic whistler detector[J]. Journal of Geophysical Research: Space Physics, 2008, 113(A12): A12201
    [37]
    LIU S T, HUANG D, WANG Y H. Receptive field block net for accurate and fast object detection[C]//Proceedings of the 15th European Conference on Computer Vision (ECCV). Munich: Springer, 2018: 385-400
    [38]
    SHEN X H, ZONG Q G, ZHANG X M. Introduction to special section on the China Seismo-Electromagnetic Satellite and initial results[J]. Earth and Planetary Physics, 2018, 2(6): 439-443. doi: 10.26464/epp2018041
    [39]
    WANG Q, HUANG J P, ZHANG X M, et al. China Seismo-Electromagnetic Satellite search coil magnetometer data and initial results[J]. Earth and Planetary Physics, 2018, 2(6): 462-468
    [40]
    YAN R, SHEN X H, HUANG J P, et al. Examples of unusual ionospheric observations by the CSES prior to earthquakes[J]. Earth and Planetary Physics, 2018, 2(6): 515-526. doi: 10.26464/epp2018050
    [41]
    ZÁHLAVA J, NĚMEC F, PINCON J L, et al. Whistler influence on the overall very low frequency wave intensity in the upper ionosphere[J]. Journal of Geophysical Research: Space Physics, 2018, 123(7): 5648-5660 doi: 10.1029/2017JA025137
    [42]
    ZHIMA Z, HUANG J P, SHEN X H, et al. Simultaneous observations of ELF/VLF rising-tone quasiperiodic waves and energetic electron precipitations in the high-latitude upper ionosphere[J]. Journal of Geophysical Research: Space Physics, 2020, 125(5): e2019JA027574. doi: 10.1029/2019ja027574
    [43]
    ZHOU B, YANG YY, ZHANG YT, et al. Magnetic field data processing methods of the China Seismo-Electromagnetic Satellite[J]. Earth and Planetary Physics, 2018, 2(6): 455-461. doi: 10.26464/epp2018043
    [44]
    ZHOU R X, GU X D, YANG K X, et al. A detailed investigation of low latitude tweek atmospherics observed by the WHU ELF/VLF receiver: I. automatic detection and analysis method[J]. Earth and Planetary Physics, 2020, 4(2): 120-130. doi: 10.26464/epp2020018
    [45]
    HUANG X D, ACERO A. Spoken Language Processing: A Guide to Theory, Algorithm, and System Development[M]. Upper Saddle River: Prentice Hall PTR, 2001
    [46]
    NĚMEC F, SANTOLÍK O, PARROT M, et al. 与地震活动相关的电磁扰动的空间观测[J]. 何宇飞, 译. 世界地震译丛, 2008(6): 39-43 doi: 10.16738/j.cnki.issn.1003-3238.2008.06.008

    NĚMEC F, SANTOLÍK O, PARROT M, et al. Spacecraft observations of electromagnetic perturbations connected with seismic activity[J]. HE Yufei, trans. Translated World Seismology, 2008(6): 39-43 doi: 10.16738/j.cnki.issn.1003-3238.2008.06.008
    [47]
    HARID V, LIU C, PANG Y, et al. Automated large‐scale extraction of whistlers using mask‐scoring regional convolutional neural network[J]. Geophysical Research Letters, 2021, 48(15): e2021GL093819 doi: 10.1029/2021GL093819
    [48]
    罗旭东, 牛胜利, 左应红, 等. 基于AKEBONO哨声波参数的内辐射带高能电子扩散模拟[J]. 计算物理, 2017, 34(3): 335-343

    LUO Xudong, NIU Shengli, ZUO Yinghong, et al. Diffusing loss effects of inner radiation belt energetic electrons based on AKEBONO whistler wave parameters[J]. Chinese Journal of Computational Physics, 2017, 34(3): 335-343
    [49]
    冯小康, 袁静, 王桥, 刘海军, 韩莹, 赵晨旭, 丰继林, 申旭辉, 泽仁志玛, 黄建平, 王亚丽. 2023. 基于人工智能的张衡卫星闪电哨声波物理参数自动提取[J/OL]. 地球物理学进展, 2023, 38(6): 2373-2391.

    FENG Xiaokang, YUAN Jing, WANG Qiao, et al. Automatic extraction of physical parameters of lightning whistler recorded by search coil magnetometer onboard ZhangHeng Satellite[J/OL]. Progress in Geophysics, 2023, 38(6): 2373-2391
    [50]
    王兰炜, 胡哲, 申旭辉, 等. 电磁监测试验卫星(张衡一号)数据处理方法和流程[J]. 遥感学报, 2018, 22(S1): 39-55

    WANG Lanwei, HU Zhe, SHEN Xuhui, et al. Data processing methods and procedures of CSES satellite[J]. Journal of Remote Sensing, 2018, 22(S1): 39-55
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