The China-France Oceanography Satellite (CFOSAT) was successfully launched on October 29, 2018, which carried two innovative payloads, i.e., the surface waves investigation and monitoring (SWIM) instrument and the rotating fan beam scatterometer (RFSCAT). CFOSAT scatterometer (CSCAT) is dedicated to the monitoring of sea surface wind vectors and variety of climate studies, but also provides useful data for the applications over land and polar regions. CSCAT employs a “rotationg fan-beam” design rather than “pen-beam” approach previously used with SeaWinds on NASA QuikSCAT and “fixed fan-beam” approach with ASCAT on METOP-A. The CSCAT produces large overlaps on the observation regions within the total swath by successive sweeps and provides a large number of backscatter acquisitions with diverse azimuth and elevation combinations for a single surface resolution cell. In order to obation higher resolution and precise backscatter of rotating fan-beam scatterometer, however, some special considerations have been made in the design of CSCAT signal and data processing. In this paper, the data processing approach of CSCAT are proposed completely for the first time. The geolocation reference mapping model is employed in CSCAT slice geolocation. In noise processing, CSCAT adopts the method of weighted least square polynomial surface fitting to conduct the adaptive noise correction factor estimation. The attitude cubic algorithm used for X integral factor computation is developed to obtain the precise backscatter coefficients based on the radar equation. Because of the high relevance between the CSCAT data processing and the hardware configuration and onboard signal processing of the instrument, the instrument module configuration and signal processing design are also analyzed and presented comprehensively. Especially, the influence and compensation of Doppler frequency on signal processing and range filtering processing are introduced. The instrument performance and data processing algorithm are verified by the accuracy analysis on the CSCAT backscattering coefficient data. The backscatter coefficient accuracy is estimation on the Amazon forest, and the results shows that the backscattering coefficient accuracy of CSCAT on 25km × 25km grid is less than 0.5dB except that the near end and far end of the beam are slightly higher. The statistical results of wind field obtained from the backscattering coefficient inversion of CSCAT are also provided, and the better wind field inversion results are obtained based on the CSCAT backscattering coefficient measurement.