The Central Weather Bureau in Taiwan successfully implemented a version of WRF coined as TWRF (Typhoon WRF) as the operational typhoon prediction system. The TWRF has two nested domains with 15/3km resolution covering large areas over the western North Pacific, which has led to significant improvements of typhoon predictions over the previous version with coarser resolutions. Built upon this success, the WRF Four-Dimensional Data Assimilation (FDDA) system has been implemented in TWRF. This study investigates the impact of assimilating dual-Doppler radar retrieval winds from eight sets of dual-Doppler radars using FDDA on the prediction of Typhoon Nesat (2017) that passed over Taiwan. The wind field retrieved with dual-Doppler radars has a vertical extent from 1 to 10 km and the horizontal resolution is 1 km. After quality control and data thinning, the radar retrieval winds are assimilated using FDDA for two update cycles in addition to the existing hybrid 3DEnVar for all other observations in TWRF. Furthermore, we assimilate the additional radar data that become available during the 4-hour waiting period for the completion of the global model prediction to be used as the lateral boundary condition for TWRF. For Typhoon Nesat, the wind structure and rainfall forecasts are improved with the assimilation of radar-retrieval winds. The overall improvements demonstrated by this case study suggest potentially high impacts for improving the prediction of typhoon-related rainfall with assimilation of dual-Doppler radar data.