Intellectual Property India Publishes Patent Application for Investigation Of Near-Surface Lunar Plasma And Earth-Ionosphere Coupling Mechanisms From Chandrayaan-3 And Gnss Tec Observations

MUMBAI, India, Aug. 31 -- Intellectual Property India has published a patent application (202641099018 A) filed by Venkata Ratnam D; and Koneru Laksmaiah Education Foundation on August 17, 2026, for Investigation Of Near-Surface Lunar Plasma And Earth-Ionosphere Coupling Mechanisms From Chandrayaan-3 And Gnss Tec Observations.

Inventors include D. Venkata Ratnam; Dr. M. Sridhar; and Dr. E. Suneetha.

The application for the patent was published on August 28, 2026, under issue no. 35/2026.

Abstract: First-time Chandrayaan-3 lander’s Radio Anatomy of the Moon-Bound Hypersensitive ionosphere and Atmosphere-Langmuir Probe (RAMBHA-LP) provides lunar data to investigate features of the lunar near-surface plasma environment. The temporal evolution of lunar plasma at the surface, including electron density and temperature data, in response to the Moon’s orbital position and external space-weather drivers (Solar Wind flux fluctuations and magnetospheric particle fluxes) will be thoroughly analyzed using RAMBHA-LP data and Earth’s ionosphere observations. The RAMBHA-LP data with Earth's ionosphere, specifically utilizing GNSS Ionospheric TEC data, provides an opportunity to reveal the correlation features of Earth’s ionosphere with lunar tidal beat phenomena with a period of 14.7653 days and lunar RAMBHA LP electron density and temperature of the lunar ionosphere. The lunar plasma electron density and temperature data retrieval are carried out. However, there is a need to enhance the reliability of electron density and temperature estimation, which typically relies on the Maxwellian electron distribution assumption by fitting the resultant curve to classical Orbital Motion Limited (OML) theory. In this research, AI/ML techniques will be implemented to estimate the mean ionospheric electron density in the range of 380–600/cc and the mean ionospheric temperature in the range of 3000–8000 K. The localized RAMBHA-LP ionospheric data and ground-based GNSS TEC data will be analysed to investigate the large-scale drivers that affect the near-surface lunar ionosphere. AI/ML unsupervised classification (High-Energy Transient Events (CMEs and SEPs) of Non-Maxwellian Plasma States will be implemented with ACE L1 Space Weather Satellites to characterize the lunar plasma state during hazardous space weather conditions.

Disclaimer: Curated by HT Syndication.