The First Flare Observation with a New Solar Microwave Spectrometer Working in 35–40 GHz

Yan, Fabao; Wu, Zhao; Shang, Ziqian; Wang, Bing; Zhang, Lei; Chen, Yao

doi:10.3847/2041-8213/acad02

Cited by 13 publications

(10 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method is called "external calibration." According to the 35-40 GHz solar radio dynamic spectrum observation system of the CSO and the theoretical radiation temperature of the Sun in the 40 GHz band, the radiation flux of the Sun in the 40 GHz band is calculated to be approximately 3000 sfu (Yan et al 2023). As shown in Figure 14, the difference in the amplitude of the visibility function obtained from the two-element interferometer pointing at the cold sky and the quiet Sun linearly corresponds to the radiation flux of the Sun in the 40 GHz band.…”

Section: Calibrationmentioning

confidence: 99%

A Two-element Interferometer for Millimeter-wave Solar Flare Observations

Yu¹,

Zhang³

et al. 2023

ApJS

Self Cite

View full text Add to dashboard Cite

In this paper, we present the design and implementation of a two-element interferometer operating in the millimeter-wave band (39.5–40 GHz) for observing solar radio emissions through nulling interference. The system is composed of two 50 cm aperture Cassegrain antennas installed on a common equatorial mount, with a separation of 230 wavelengths. The cross-correlation of the received signals effectively cancels out the quiet solar component of the high flux density (∼3000 sfu) that reduces the detection limit due to atmospheric fluctuations. The system performance is as follows: the noise factor of the analog front end in the observation band is less than 2.1 dB, system sensitivity is approximately 12.4 K (∼34 sfu) with an integration time constant of 0.1 ms (default), the frequency resolution is 153 kHz, and the dynamic range is ≥30 dB. Through actual testing, the nulling interferometer observes a quiet Sun with a low level of output fluctuations (up to 50 sfu) and has a significantly lower radiation flux variability (up to 190 sfu) than an equivalent single-antenna system, even under thick cloud cover. As a result, this new design can effectively improve observation sensitivity by reducing the impact of atmospheric and system fluctuations during observation.

show abstract

Section: Calibrationmentioning

confidence: 99%

A Two-element Interferometer for Millimeter-wave Solar Flare Observations

Yu¹,

Zhang³

et al. 2023

ApJS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, two methods are used to calibrate the system. The first method performs relative calibration on the data, and the second method performs calibration using noise source (Du et al 2017;Yan et al 2023). The international similar observation data contain multiple frequency points, such as 8.8 GHz and 9.4 GHz, which coincide with the solar radio observation system of 6-15 GHz.…”

Section: Data Calibrationmentioning

confidence: 99%

A New 6–15 GHz Solar Radio Observation System

Zhang 张,

Su 苏,

Wu 武

et al. 2023

ApJS

Self Cite

View full text Add to dashboard Cite

In this study, we have developed a centimeter-band solar radio telescope covering the 6–15 GHz frequency band. The radio telescope has the outstanding advantages of a large instantaneous sampling bandwidth and wide frequency coverage. As a new solar radio telescope, its time resolution reaches a very high level of 0.26 ms at a frequency resolution of 3 MHz, which is very conducive to observing the fine structure of radio burst signals. In terms of the structure design, the system employs a 3 m diameter parabolic antenna to receive solar radio signals. The antenna has high gain and good directivity, and the pointing accuracy reaches 0.°02, which ensures the ability to accurately track the Sun in real time. In the analog signal processing module, the combination of radio frequency direct acquisition and down conversion is used to reduce the interference caused by multiple spectrum shifts. Regarding the digital receiver, a digital receiving module with high sampling rate and acquisition resolution is used for data acquisition and processing, which ensures that the observation system can obtain observation data with high time and frequency resolutions and real-time data processing. During the trial operation of the system, solar radio bursts have been observed many times, and these observations have been supported by similar international observation equipment. According to a data comparison, the data obtained by our observation system are more precise. At present, equipment calibration methods are being improved and constructed to obtain more accurate observation data.

show abstract

“…As a result, many solar radio observation devices have been created, such as the 35-40 GHz spectral observation system of Shandong University [2]. They first flare (the X2.2 flare on 2022, April 20) was observed using of the newly built Chashan Broadband Solar millimeter spectrometer (CBS) working from 35 to 40 GHz [3]. After identifying specific outburst regions in the solar radio spectrogram, researchers can analyze outburst event durations, starting and ending frequencies, outburst intensity, frequency drift rate, frequency bandwidth occupied by outburst events and their harmonic ratios, and other parameters for in-depth study of the solar radio [4].…”

Section: Introductionmentioning

confidence: 99%

Solar radio spectrogram segmentation algorithm based on improved fuzzy C-means clustering and adaptive cross filtering

Liu,

Shen,

Song

et al. 2024

Phys. Scr.

Self Cite

View full text Add to dashboard Cite

Solar radio spectrograms contain essential information, such as the duration type; therefore, recognizing and detecting solar radio spectrograms are significant for the further study of solar radio. With the upgrading of solar radio observation, considering the equipment that has already generated amounts of data, researchers have begun to use machine learning methods to recognize and detect solar radio spectrograms to resolve the weaknesses of manual identification, such as time consumption. However, the spectrograms are characterized by noise or insignificant outburst features, which affect the recognition and detection of solar radio spectrograms. In contrast, extracting the burst region separately and the more distinctive spectrogram features will help identify and detect it. Therefore, to remove the burst domain of the radio spectrogram better, this paper combines the idea of image segmentation and proposes a solar radio spectrogram segmentation algorithm based on improved fuzzy C-means (FCM) clustering and adaptive cross filtering for the extraction of the burst domain of solar radio spectrograms. This algorithm has multiple processing steps. The first step is solar radio spectrogram segmentation with the improved FCM based on the kernel-induced distance by incorporating spatial constraints combined with random walk and adaptive affiliation linking (RWAKFCM_S). The second step is adaptive cross filtering, eliminating the noise clustered in bursts. The results show the following. (1) The RWAKFCM_S proposed in this paper has better anti-noise and segmentation performance than other methods in the synthetic, natural, and solar radio spectrogram segmentation experiments; it can also overcome the problems of noise sensitivity when segmenting spectrograms by traditional FCM. (2) The RWAKFCM_S can satisfy the high accuracy and rate of solar radio spectrogram segmentation demands. (3) The adaptive cross filtering proposed in this paper can eliminate noise clustered in the eruption domain. (4) The proposed method enables burst region extraction。

show abstract

The First Flare Observation with a New Solar Microwave Spectrometer Working in 35–40 GHz

Cited by 13 publications

References 47 publications

A Two-element Interferometer for Millimeter-wave Solar Flare Observations

A Two-element Interferometer for Millimeter-wave Solar Flare Observations

A New 6–15 GHz Solar Radio Observation System

Solar radio spectrogram segmentation algorithm based on improved fuzzy C-means clustering and adaptive cross filtering

Contact Info

Product

Resources

About