Based on a statistical analysis of the currently available 3-year on-orbit Cyclone Global Navigation Satellite System (CYGNSS) data (2017–2019), this study proposes a two-step calibration method to improve the accuracy of the CYGNSS-derived land surface reflectivity (SR) and the resulting soil moisture (SM) estimates. The method is designed for two purposes: the one is to correct the system errors of the SR estimates induced by the calibration of the CYGNSS Version 2.1 L1B data, and the other is to eliminate vegetation attenuation in the SR of the soil layer. Mean SR corrections of ~ −0.9 and 2.2 dB are achieved through the first and second steps of calibration, respectively. This resulted in better SM estimates compared with the Soil Moisture Active Passive (SMAP) product and the <italic>in situ</italic> measurements, i.e., improved correlations between the CYGNSS SR and the SMAP SM (from <inline-formula> <tex-math notation="LaTeX">$R = 0.46$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$R = 0.74$ </tex-math></inline-formula>), improved correlations between the CYGNSS SR and the <italic>in situ</italic> SM (from <inline-formula> <tex-math notation="LaTeX">$R = 0.47$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$R = 0.62$ </tex-math></inline-formula>), and between the CYGNSS SM and the <italic>in situ</italic> SM with the best <inline-formula> <tex-math notation="LaTeX">$R = 0.64$ </tex-math></inline-formula>.