Characterizing and Mitigating Digital Sampling Effects on the CYGNSS Level 1 Calibration

Abstract

This article presents a detailed examination of fluctuating input noise power levels on the analog-to-digital convertor (ADC) sampling hardware of the NASA Cyclone Global Navigation Satellite System (CYGNSS) instruments and the associated impacts on the level 1 normalized bistatic radar cross section (NBRCS) estimation performance. The impact of external noise variations on both the CYGNSS science and navigation channels is quantified with respect to how the fluctuating received power impacts the low-level ADC sampling distribution and subsequent NBRCS estimation. This work demonstrates that there are clear quantifiable geospatially dependent noise variations linked to Global Navigation Satellite System (GNSS) space-based augmentation systems [notably Japanese Quasi-Zenith Satellite System (QZSS) and U.S. Wide Area Augmentation System (WAAS)] and that these additional noise sources significantly alter the digital sampling distribution of the CYGNSS instruments, actively degrading the level 1 NBRCS estimation if not corrected. A derivation of the theoretical correction for both the science and navigation channel ADC sampling variations is presented which is later tuned based on empirical performance metrics in an effort to minimize the induced calibration errors. The impacts of the enhancements outlined in this work on CYGNSS level 1 calibration are evaluated using one year of observations before and after the digital sampling corrections, using model European Centre for Medium-Range Weather Forecasts (ECMWF) wind and Wavewatch III mean square slope (MSS) surface validation datasets.