YTYanyan Tang

Yanyan Tang

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Yanyan Tang has a total of 13 co-authors. Here are the top co-authors by number of shared publications:

  • Hao Han

    Planetary Environmental and Astrobiological Research Laboratory (PEARL), School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai 519082, China

    2 shared publications
  • Jiahao Zhong

    Planetary Environmental and Astrobiological Research Laboratory (PEARL) School of Atmospheric Sciences Sun Yat‐sen University Zhuhai China

    2 shared publications
  • Jiawen Chen

    Planetary Environmental and Astrobiological Research Laboratory (PEARL), School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai 519082, China

    2 shared publications
  • Kang Wang

    Shanghai Radio Equipment Research Institute, Shanghai 201109, China

    2 shared publications
  • Wenyu Du

    Planetary Environmental and Astrobiological Research Laboratory (PEARL), School of Atmospheric Sciences, Sun Yat-Sen University, Zhuhai 519082, China

    2 shared publications
  • Xin Wan

    Planetary Environmental and Astrobiological Research Laboratory (PEARL), School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China

    2 shared publications

Latest Publications

  • Open Access

    Near-Real-Time Global Thermospheric Density Variations Unveiled by Starlink Ephemeris

    by Zhuoliang Ou, Jiahao Zhong, Yongqiang Hao, Ruoxi Li, Xin Wan, Kang Wang, Jiawen Chen, Hao Han, Xingyan Song, Wenyu Du, et al.

    Previous efforts to retrieve thermospheric density using satellite payloads have been limited to a small number of satellites equipped with GNSS (Global Navigation Satellite System) receivers and accelerometers. These satellites are confined to a few orbital planes, and analysis can only be conducted after the data are processed and updated, resulting in sparse and delayed thermospheric density datasets. In recent years, the Starlink constellation, developed and deployed by SpaceX, has emerged as the world’s largest low Earth orbit (LEO) satellite constellation, with over 6000 satellites in operations as of October 2024. Through the strategic use of multiple orbital shells featuring various inclinations and altitudes, Starlink ensures continuous near-global coverage. Due to extensive coverage and frequent maneuvers, SpaceX has publicly released predicted ephemeris data for all Starlink satellites since May 2021, with updates approximately every 8 h. With the ephemeris data of Starlink satellites, we first apply a maneuver detection algorithm based on mean orbital elements to analyze their maneuvering behavior. The results indicate that Starlink satellites exhibit more frequent maneuvers during thermospheric disturbances. Then, we calculate the mechanical energy loss caused by non-conservative forces (primarily atmospheric drag) through precise dynamical models. The results demonstrate that, despite certain limitations in Starlink ephemeris data, the calculated mechanical energy loss still effectively captures thermospheric density variations during both quiet and disturbed geomagnetic periods. This finding is supported by comparisons with Swarm-B data, revealing that SpaceX incorporates the latest space environment conditions into its orbit extrapolation models during each ephemeris update. With a maximum lag of only 8 h, this approach enables near-real-time monitoring of thermospheric density variations using Starlink ephemeris.


  • Open Access

    Effects of Equatorial Plasma Bubbles on Multi-GNSS Signals: A Case Study over South China

    by Hao Han, Jiahao Zhong, Yongqiang Hao, Ningbo Wang, Xin Wan, Fuqing Huang, Qiaoling Li, Xingyan Song, Jiawen Chen, Kang Wang, et al.

    Equatorial plasma bubbles (EPBs) occur frequently in low-latitude areas and have a non-negligible impact on navigation satellite signals. To systematically analyze the effects of a single EPB event on multi-frequency signals of GPS, Galileo, GLONASS, and BDS, all-sky airglow images over South China are jointly used to visually determine the EPB structure and depletion degree. The results reveal that scintillations, or GNSS signal fluctuations, are directly linked to EPBs and that the intensity of scintillation is positively correlated with the airglow depletion intensity. The center of the airglow depletion often corresponds to stronger GNSS scintillation, while the edge of the bubble, which is considered to have the largest density gradient, corresponds to relatively smaller scintillation instead. This work also systematically analyzes the responses of multi-constellation and multi-frequency signals to EPBs. The results show that the L2 and L5 frequencies are more susceptible than the L1 frequency is. For different constellations, Galileo’s signal has the best tracking stability during an EPB event compared with GPS, GLONASS, and BDS. The results provide a reference for dual-frequency signal selection in precise positioning or TEC calculation, that is, L1C and L2L for GPS, L1C and L5Q for Galileo, L1P and L2C for GLONASS, and L1P and L5P for BDS. Notably, BDS-2 is significantly weaker than BDS-3. And inclined geosynchronous orbit (IGSO) satellites have abnormal data error rates, which should be related to the special signal path trajectory of the IGSO satellite.