Session B3: Technologies for Scientific and Sectorial Applications

On-Orbit Performance of the TRITON GNSS-R Payload
Jyh-Ching Juang, Department of Electrical Engineering, National Cheng Kung University
Date/Time: Thursday, Sep. 19, 11:03 a.m.

In recent years, several GNSS reflectometry missions including the celebrated CYGNSS have been conducted to explore the potential of omni-presence and high-quality GNSS signals for remote sensing applications of the surface of the Earth. The TRITON mission represents a new entry to this echelon in measuring the scattered signals from GNSS satellites in low-earth orbit. The TASA’s TRITON microsatellite was launched in October, 2023 and the mission objective is to perform GNSS reflectometry experiments in a hope to enhance the predication capability of typhoons. This mission was motivated by the FORMOSAT-7 and CYGNSS missions. Indeed, the TRITON GNSS-R mission was conceived to complement existing FORMOSAT-7 GNSS radio occultation mission for a better understanding of the air-sea interactions, especially during severe weather by observing scattered GNSS signals. The main payload of the TRITON is an GNSS receiver that is capable of receiving and processing scattered GNSS signals from the surface of the Earth. Currently, the function and performance of the GNSS-R payload have essentially been verified. The calibrated GNSS-R data of the TRITON are expected to be openly available before Q2, 2024. The paper presents on-orbit results of the TRITON GNSS-R receiver payload encompassing the analysis of the quality of the delay Doppler maps which are the main observable of the GNSS-R payload, the observation of the scattering GNSS signals by using the payload, and the calibration procedure and preliminary results for wind retrieval. A difference between the TRITON GNSS-R payload with some existing ones is that the delay Doppler map (DDM) has a wide range of 128 code phase delays and 64 Doppler shift bins. This enables the use of 1D waveform-based or 2D image-based data processing. Some work on the development of waveform-based or image-based retrieval methods will be discussed.