Geomagnetic activity with global influence is an essential object of space weather research and is a significant link in the section of the solar wind-magnetospheric coupling process. Research so far provides strong evidence that geomagnetic activity affects stock investment decisions by influencing human health, mood, and human behaviours. Therefore, this research investigates the empirical association between geomagnetic activity and stock market return. Overall, we find that geomagnetic activity exerts a negative influence on the return of the US stock market. Further, market liquidity effectively magnifies the effect of geomagnetic activity. Inconsistent with previous literature, this effect is not mainly caused by the semiannual variation of geomagnetic activity. Our research contributes to the introduction of geomagnetic indices to financial economics studies on the impact of geomagnetic activity influence on stock market return.
{"title":"Effect of Ap-Index of Geomagnetic Activity on S&P 500 Stock Market Return","authors":"Lifang Peng, Ning Li, Jing-cai Pan","doi":"10.1155/2019/2748062","DOIUrl":"https://doi.org/10.1155/2019/2748062","url":null,"abstract":"Geomagnetic activity with global influence is an essential object of space weather research and is a significant link in the section of the solar wind-magnetospheric coupling process. Research so far provides strong evidence that geomagnetic activity affects stock investment decisions by influencing human health, mood, and human behaviours. Therefore, this research investigates the empirical association between geomagnetic activity and stock market return. Overall, we find that geomagnetic activity exerts a negative influence on the return of the US stock market. Further, market liquidity effectively magnifies the effect of geomagnetic activity. Inconsistent with previous literature, this effect is not mainly caused by the semiannual variation of geomagnetic activity. Our research contributes to the introduction of geomagnetic indices to financial economics studies on the impact of geomagnetic activity influence on stock market return.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/2748062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48539334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Automatic detection of solar events, especially uncommon events such as coronal dimming (CD) and coronal wave (CW), is very important in solar physics research. The CD and CW are not only related to the detection of coronal mass ejections (CMEs) but also affect space weather. In this paper, we have studied methods for automatically detecting them. In addition, we have collected and processed a dataset that includes the solar images and event records, where the solar images come from the Atmospheric Imaging Assembly (AIA) of Solar Dynamics Observatory (SDO) and the event records come from Heliophysics Event Knowledgebase (HEK). Different from the methods used before, we introduce the idea of deep learning. We train single-wavelength and multiwavelength models based on Faster R-CNN. In terms of accuracy, the single-wavelength model performs better. The multiwavelength model has a better detection performance on multiple solar events than the single-wavelength model.
{"title":"Single and Multiwavelength Detection of Coronal Dimming and Coronal Wave Using Faster R-CNN","authors":"Zong-You Xie, Chunyan Ji","doi":"10.1155/2019/7821025","DOIUrl":"https://doi.org/10.1155/2019/7821025","url":null,"abstract":"Automatic detection of solar events, especially uncommon events such as coronal dimming (CD) and coronal wave (CW), is very important in solar physics research. The CD and CW are not only related to the detection of coronal mass ejections (CMEs) but also affect space weather. In this paper, we have studied methods for automatically detecting them. In addition, we have collected and processed a dataset that includes the solar images and event records, where the solar images come from the Atmospheric Imaging Assembly (AIA) of Solar Dynamics Observatory (SDO) and the event records come from Heliophysics Event Knowledgebase (HEK). Different from the methods used before, we introduce the idea of deep learning. We train single-wavelength and multiwavelength models based on Faster R-CNN. In terms of accuracy, the single-wavelength model performs better. The multiwavelength model has a better detection performance on multiple solar events than the single-wavelength model.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/7821025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47145766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recent Advances in Lunar Exploration Using Radar and Microwave Techniques","authors":"Jing Li, Z. Meng, A. Gusev","doi":"10.1155/2019/4794258","DOIUrl":"https://doi.org/10.1155/2019/4794258","url":null,"abstract":"","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/4794258","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47012783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Lunar Penetrating Radar (LPR) is one of the important scientific payloads in China’s Chang’E-3 (CE-3) to image within 100 m below the lunar surface. The acquired LPR data is significant for the research of lunar geological structure. Based on the sedimentary mechanism of lunar regolith, the regolith contains many rocks with different sizes. These local anomalies appear as diffraction in LPR data, which reduces the data quality and limits the structural analysis of lunar regolith. According to the kinematics characteristics of rock caused diffraction, we transform these problems to a problem of steep dip decreasing. To reach this goal, we adopt a data preprocessing workflow to improve the quality of the radar image, firstly. Then, a dip filter based on adaptive f-x empirical mode decomposition (EMD) is proposed to extract the rocks in the regolith and the corresponding removed IMF map indicates the degree of rock enrichment and highlights regolith-basement interface. Both simulation and LPR CH-2 data present a great performance. Finally, according to the processed result, we locate the position of each rock and highlight the contact interface of regolith and the basement rock.
{"title":"Structural Analysis of Lunar Regolith from LPR CH-2 Data Based on Adaptive f-x E MD: LPR Data Processed by Adaptive f-x EMD","authors":"Bin Hu, Deli Wang, Ling Zhang, Z. Zeng","doi":"10.1155/2019/1528410","DOIUrl":"https://doi.org/10.1155/2019/1528410","url":null,"abstract":"The Lunar Penetrating Radar (LPR) is one of the important scientific payloads in China’s Chang’E-3 (CE-3) to image within 100 m below the lunar surface. The acquired LPR data is significant for the research of lunar geological structure. Based on the sedimentary mechanism of lunar regolith, the regolith contains many rocks with different sizes. These local anomalies appear as diffraction in LPR data, which reduces the data quality and limits the structural analysis of lunar regolith. According to the kinematics characteristics of rock caused diffraction, we transform these problems to a problem of steep dip decreasing. To reach this goal, we adopt a data preprocessing workflow to improve the quality of the radar image, firstly. Then, a dip filter based on adaptive f-x empirical mode decomposition (EMD) is proposed to extract the rocks in the regolith and the corresponding removed IMF map indicates the degree of rock enrichment and highlights regolith-basement interface. Both simulation and LPR CH-2 data present a great performance. Finally, according to the processed result, we locate the position of each rock and highlight the contact interface of regolith and the basement rock.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/1528410","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44317669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Meng, H. H. Wang, Y. C. Zheng, Y. Z. Wang, H. Miyamoto, Z. C. Cai, J. Ping, Y. Z. Zhu
The study on the Schrödinger basin may provide important clues about the formation of South Pole-Aitken (SPA) basin. In this paper, the thermophysical features of Schrödinger basin were evaluated using the Chang’E-2 microwave sounder (CELMS) data. The results are as follows. (1) The geological units are reevaluated with the CELMS data and a new geological view was provided according to the brightness temperature and emissivity maps. (2) The surface topography plays an important role in the observed CELMS data. (3) The hot anomaly in the basin floor indicates a warm substrate. (4) The pyroxene-bearing anorthosite is probably an important cause for the cold anomaly over the lunar surface. Also, the study proves the applicability of the CELMS data applying in high latitude regions to a certain extent.
{"title":"Several Geological Issues of Schrödinger Basin Exposed by CE-2 CELMS Data","authors":"Z. Meng, H. H. Wang, Y. C. Zheng, Y. Z. Wang, H. Miyamoto, Z. C. Cai, J. Ping, Y. Z. Zhu","doi":"10.1155/2019/3926082","DOIUrl":"https://doi.org/10.1155/2019/3926082","url":null,"abstract":"The study on the Schrödinger basin may provide important clues about the formation of South Pole-Aitken (SPA) basin. In this paper, the thermophysical features of Schrödinger basin were evaluated using the Chang’E-2 microwave sounder (CELMS) data. The results are as follows. (1) The geological units are reevaluated with the CELMS data and a new geological view was provided according to the brightness temperature and emissivity maps. (2) The surface topography plays an important role in the observed CELMS data. (3) The hot anomaly in the basin floor indicates a warm substrate. (4) The pyroxene-bearing anorthosite is probably an important cause for the cold anomaly over the lunar surface. Also, the study proves the applicability of the CELMS data applying in high latitude regions to a certain extent.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/3926082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45382325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
China Chang’E-3 performed soft landing at the plains of Sinus Iridum on lunar surface on December 14th 2013 successfully; it opened a new window for observing lunar surface with radiometric tracking which many lunar scientific researchers always pursue for. Since July 2014, OCEL (Observing Chang’E-3 Lander with VLBI) project has been conducted jointly by IVS (International VLBI Service of Geodesy and Astrometry) and BACC (Beijing Aerospace Control Center), a global IVS R&D network augmented with two China Deep Space Stations configured for OCEL. This paper presents the current status and preliminary result of the OCEL and mainly focuses on determination of the lander position, which is about 7 meter in height and 14 meter in plane of lunar surface with respect to LRO (Lunar Reconnaissance Orbiter). Based on accuracy analysis, further optimized OCEL sessions will make use of this target-of-opportunity, the Chang’E-3 lunar lander, as long as it is working. With higher accurate radiometric observables, more prospective contribution to earth and lunar science is expected by combining with LLR.
{"title":"Lunar Radiometric Measurement Based on Observing China Chang’E-3 Lander with VLBI—First Insight","authors":"Song-tao Han, Zhongkai Zhang, Jing Sun, Jianfeng Cao, Lue Chen, Weitao Lu, Wenxiao Li","doi":"10.1155/2019/7018620","DOIUrl":"https://doi.org/10.1155/2019/7018620","url":null,"abstract":"China Chang’E-3 performed soft landing at the plains of Sinus Iridum on lunar surface on December 14th 2013 successfully; it opened a new window for observing lunar surface with radiometric tracking which many lunar scientific researchers always pursue for. Since July 2014, OCEL (Observing Chang’E-3 Lander with VLBI) project has been conducted jointly by IVS (International VLBI Service of Geodesy and Astrometry) and BACC (Beijing Aerospace Control Center), a global IVS R&D network augmented with two China Deep Space Stations configured for OCEL. This paper presents the current status and preliminary result of the OCEL and mainly focuses on determination of the lander position, which is about 7 meter in height and 14 meter in plane of lunar surface with respect to LRO (Lunar Reconnaissance Orbiter). Based on accuracy analysis, further optimized OCEL sessions will make use of this target-of-opportunity, the Chang’E-3 lunar lander, as long as it is working. With higher accurate radiometric observables, more prospective contribution to earth and lunar science is expected by combining with LLR.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/7018620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49182247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Measurements of the disk-integrated brightness temperature of the Moon at 89, 157, 183, and 190 GHz are presented for phase angles between -80° and 50° relative to full Moon. They were obtained with the Microwave Humidity Sounder (MHS) on NOAA-18 from 39 instances when the Moon appeared in the deep space view of the instrument. Polynomials were fitted to the measured values and the maximum temperature and the phase angle of its occurrence were determined. A comparison of these results with the predictions from three different models or rather parametrical expressions by Keihm, Mo & Kigawa, and Yang et al. revealed significantly larger phase lags for the lower frequencies in the measurements with MHS. As the Moon has appeared thousands of times in the field of view of all microwave sounders combined, this investigation demonstrates the potential of weather satellites for fine tuning models and establishing the Moon as extremely accurate calibration reference.
{"title":"Disk-Integrated Lunar Brightness Temperatures between 89 and 190 GHz","authors":"M. Burgdorf, S. Buehler, I. Hans, M. Prange","doi":"10.1155/2019/2350476","DOIUrl":"https://doi.org/10.1155/2019/2350476","url":null,"abstract":"Measurements of the disk-integrated brightness temperature of the Moon at 89, 157, 183, and 190 GHz are presented for phase angles between -80° and 50° relative to full Moon. They were obtained with the Microwave Humidity Sounder (MHS) on NOAA-18 from 39 instances when the Moon appeared in the deep space view of the instrument. Polynomials were fitted to the measured values and the maximum temperature and the phase angle of its occurrence were determined. A comparison of these results with the predictions from three different models or rather parametrical expressions by Keihm, Mo & Kigawa, and Yang et al. revealed significantly larger phase lags for the lower frequencies in the measurements with MHS. As the Moon has appeared thousands of times in the field of view of all microwave sounders combined, this investigation demonstrates the potential of weather satellites for fine tuning models and establishing the Moon as extremely accurate calibration reference.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/2350476","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43179532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Zhu, W. Liu, B. Y. Wang, M. Zhang, W. Tian, X. Yu, T. Liang, D. Wu, D. Hu, F. Duan
Filaments are a type of wide-existing astronomical structure. It is a challenge to separate filaments from radio astronomical images, because their radiation is usually weak. What is more, filaments often mix with bright objects, e.g., stars, which makes it difficult to separate them. In order to extract filaments, A. Men’shchikov proposed a method “getfilaments” to find filaments automatically. However, the algorithm removed tiny structures by counting connected pixels number simply. Removing tiny structures based on local information might remove some part of the filaments because filaments in radio astronomical image are usually weak. In order to solve this problem, we applied morphology components analysis (MCA) to process each singe spatial scale image and proposed a filaments extraction algorithm based on MCA. MCA uses a dictionary whose elements can be wavelet translation function, curvelet translation function, or ridgelet translation function to decompose images. Different selection of elements in the dictionary can get different morphology components of the spatial scale image. By using MCA, we can get line structure, gauss sources, and other structures in spatial scale images and exclude the components that are not related to filaments. Experimental results showed that our proposed method based on MCA is effective in extracting filaments from real radio astronomical images, and images processed by our method have higher peak signal-to-noise ratio (PSNR).
{"title":"Extracting Filaments Based on Morphology Components Analysis from Radio Astronomical Images","authors":"M. Zhu, W. Liu, B. Y. Wang, M. Zhang, W. Tian, X. Yu, T. Liang, D. Wu, D. Hu, F. Duan","doi":"10.1155/2019/2397536","DOIUrl":"https://doi.org/10.1155/2019/2397536","url":null,"abstract":"Filaments are a type of wide-existing astronomical structure. It is a challenge to separate filaments from radio astronomical images, because their radiation is usually weak. What is more, filaments often mix with bright objects, e.g., stars, which makes it difficult to separate them. In order to extract filaments, A. Men’shchikov proposed a method “getfilaments” to find filaments automatically. However, the algorithm removed tiny structures by counting connected pixels number simply. Removing tiny structures based on local information might remove some part of the filaments because filaments in radio astronomical image are usually weak. In order to solve this problem, we applied morphology components analysis (MCA) to process each singe spatial scale image and proposed a filaments extraction algorithm based on MCA. MCA uses a dictionary whose elements can be wavelet translation function, curvelet translation function, or ridgelet translation function to decompose images. Different selection of elements in the dictionary can get different morphology components of the spatial scale image. By using MCA, we can get line structure, gauss sources, and other structures in spatial scale images and exclude the components that are not related to filaments. Experimental results showed that our proposed method based on MCA is effective in extracting filaments from real radio astronomical images, and images processed by our method have higher peak signal-to-noise ratio (PSNR).","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/2397536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47060650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The solar radio flux at 10.7cm (F10.7) is a direct monitor and an important indicator of solar variability, and F10.7 is commonly used in empirical atmospheric models, ionosphere models, etc. The source regions of F10.7 are mainly in the corona above the active regions, and the extreme ultraviolet (EUV) images reflect the coronal thermal structure. In this paper, an index is defined as PSR based on the intensity values of solar EUV images to represent the coronal contribution to F10.7. The Spearman correlation coefficient between the observed values of F10.7 and PSR is 0.85 in 304 Å EUV images. Based on the high correlation, an empirical model is constructed. Combining the EUV data of SDO/AIA and the twin STEREO/EUVI, solar full-disk EUV images can be generated, and the future 27-day values of PSR can be calculated. Then, a realistic estimation of F10.7 from 1 to 27 days in advance can be provided by the empirical model. Compared to the predictive values of F10.7 by the 54th-order autoregressive models in 2012-2013, the error drop-rate of our model is 12.54%, and our method has significant advantages in the upcoming 3 to 27 days’ forecast.
{"title":"The Mid-Term Forecast Method of F10.7 Based on Extreme Ultraviolet Images","authors":"L. Lei, Q. Zhong, J. Wang, L. Shi, S. Liu","doi":"10.1155/2019/5604092","DOIUrl":"https://doi.org/10.1155/2019/5604092","url":null,"abstract":"The solar radio flux at 10.7cm (F10.7) is a direct monitor and an important indicator of solar variability, and F10.7 is commonly used in empirical atmospheric models, ionosphere models, etc. The source regions of F10.7 are mainly in the corona above the active regions, and the extreme ultraviolet (EUV) images reflect the coronal thermal structure. In this paper, an index is defined as PSR based on the intensity values of solar EUV images to represent the coronal contribution to F10.7. The Spearman correlation coefficient between the observed values of F10.7 and PSR is 0.85 in 304 Å EUV images. Based on the high correlation, an empirical model is constructed. Combining the EUV data of SDO/AIA and the twin STEREO/EUVI, solar full-disk EUV images can be generated, and the future 27-day values of PSR can be calculated. Then, a realistic estimation of F10.7 from 1 to 27 days in advance can be provided by the empirical model. Compared to the predictive values of F10.7 by the 54th-order autoregressive models in 2012-2013, the error drop-rate of our model is 12.54%, and our method has significant advantages in the upcoming 3 to 27 days’ forecast.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/5604092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47606965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Solar radio images in decimeter wave range consist of many complicated components including a disk component, some bright and weak compact sources, and many diffuse features. Complicated structures combining these various components maybe cause restoration failure when using conventional algorithms. Furthermore, the images at different frequencies band are pretty different. Therefore, restoration method for solar radio image is different from other radio sources. Some image restoration methods were applied and obtained good results on Nancay radioheliograph images and Nobeyama radioheliograph images, and some new methods were introduced into processing these complicated solar radio images in recent years. For a new radioheliograph with ultrawide frequency band, new image restoration method which can maximize function of telescope is demanded. Different images could be obtained from the same visibilities data by using different weighting functions in imaging processing. In this paper, a new restoration method for solar radio image was proposed. Two images with different weighting functions from the same data are combined in this method. This restoration method has applied to data processing of Mingantu spectral radioheliograph.
{"title":"A New Image Restoration Method for MUSER","authors":"Wei Wang, Yihua Yan","doi":"10.1155/2019/8087405","DOIUrl":"https://doi.org/10.1155/2019/8087405","url":null,"abstract":"Solar radio images in decimeter wave range consist of many complicated components including a disk component, some bright and weak compact sources, and many diffuse features. Complicated structures combining these various components maybe cause restoration failure when using conventional algorithms. Furthermore, the images at different frequencies band are pretty different. Therefore, restoration method for solar radio image is different from other radio sources. Some image restoration methods were applied and obtained good results on Nancay radioheliograph images and Nobeyama radioheliograph images, and some new methods were introduced into processing these complicated solar radio images in recent years. For a new radioheliograph with ultrawide frequency band, new image restoration method which can maximize function of telescope is demanded. Different images could be obtained from the same visibilities data by using different weighting functions in imaging processing. In this paper, a new restoration method for solar radio image was proposed. Two images with different weighting functions from the same data are combined in this method. This restoration method has applied to data processing of Mingantu spectral radioheliograph.","PeriodicalId":48962,"journal":{"name":"Advances in Astronomy","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2019-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/8087405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47196416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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