A New Method of Frequency Fluctuation Estimation and IPS Processing Results Based on the Downlink Signal of Tianwen-1

RESEARCH IN ASTRONOMY AND ASTROPHYSICS(2023)

引用 0|浏览1
暂无评分
摘要
The radio-occultation observations taken by Tianwen-1 are aiming to study the properties of solar wind. A new method of frequency fluctuation (FF) estimation is presented for processing the down-link signals of Tianwen-1 during the occultation period to study the properties of the coronal plasma at the heliocentric distances of 4.48-19 R (& ODOT;). Because of low S/N as well as the phase fluctuation phenomena caused by solar activity, a Kalman based on polynomial prediction methods is proposed to avoid the phase locked loop loss lock. A new detrend method based on multi-level iteration correction is proposed to estimate Doppler shift to get more accurate power density spectra of FF in the low frequency region. The data analyze procedure is used to get the properties of the solar corona during the occultation. The method was finally verified at the point when the solar offset is 5.7 R (& ODOT;), frequency tracking was successfully performed on data with a carrier-to-noise ratio of about 28 dBHz. The density spectra obtained by the improved method are basically the same when the frequency is greater than 2 mHz, the uncertainty in the result of the rms of the FF obtained by removing the trend term with different order polynomials is less than 3.3%. The data without eliminating interference show a large error for different detrending orders, which justifies the need for an improved approach. Finally, the frequency fluctuation results combined with the information on intensity fluctuation obtained by the new method are compared with the results of the integrated Space Weather Analysis system and theoretical formula, which verifies that the processing results in this paper have a certain degree of credibility.
更多
查看译文
关键词
frequency fluctuation estimation,downlink signal,ips processing results
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要