Abstract: Sea ice concentration is one of the important parameters of sea ice, which plays an important role in ice navigation, offshore operations, sea ice model verification and climate model improvement. Satellite remote sensing has the advantages of wide coverage, short revisit period and low cost, and has become the main observation method to obtain sea ice concentration. From the perspectives of active and passive microwave remote sensing as well as optical remote sensing, this paper reviews the current research progress in satellite remote sensing retrieval of sea ice concentration, including sea ice monitoring sensors, sea ice concentration inversion algorithms, and sea ice concentration products. The results show that passive microwave remote sensing is the main method to obtain sea ice concentration at present, and many mature operational algorithms have been developed. Active microwave remote sensing data has become the main data source of sea ice charts. The sea ice concentration retrieval algorithms are developed from SAR image classification to deep learning. The sea ice concentration algorithms based on optical remote sensing are relatively mature, but limited by the clouds and the night, and their results are usually used for other products ’ validation. Limited by the sensors ’ hardware, the three observation methods have their own advantages and disadvantages. In order to obtain sea ice concentration with high precision and high spatial and temporal resolution, multi-source data fusion is an effective means to solve the bottleneck of sensor performance. As satellite remote sensing enters the era of big data, the sea ice concentration retrieval technology based on deep learning develops rapidly, which requires deep integration of satellite remote sensing knowledge of sea ice concentration. Satellite remote sensing retrieval of sea ice concentration should serve sea ice forecasting and improve the country’s sea ice forecasting ability.