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Based on the two kinds of ship-based observation data sets, we use the point-to-point method and Beitsch"s co-location comparison method to carry out a series of evaluations on the passive microwave remote sensing products (PM) for observing sea ice concentration (SIC) in the Prydz Bay, Antarctica. Considering the difference in ship-based observation data, we divided the comparison into two parts: Firstly, according to the ship-based observation data of China"s 29th, 31st, and 37th Antarctic scientific expedition in 2012-2021, eight remote sensing SIC products are classified, and quantitatively compared according to the size of SIC. The results show that NSIDC / NT2 product assesses the highest correlation and the best stability in all cases. In the co-location comparison, the correlation coefficient can reach 0.926, the root mean square error (RMSE) is 12%, and the average bias is only 2%. Secondly, to make up for the AMSR2 sensor series products" lack of historical data, we evaluate the seasonal cycle and long-term variation signals of four remote sensing data products by using the ASPeCt ship-based observation data set from 1992 to 2000 in the same way. The results show that the inversion accuracy of this period is lower than the case-by-case comparison result from 2012 to 2021, and reflects a tremendous seasonal difference. The bias of the four products increases from the melting period to the freezing period. During this period, the overall inversion of CDR and bootstrap algorithms based on SSM / I sensors are better, with correlation coefficients of more than 0.8, RMSE of 16%, and bias of about 8%. However, there remains a large bias in the low SIC region. This study shows that the accuracy of PM SIC products in a small sea area is insufficient, and fluctuates greatly with the difference in SIC type, season, and algorithm. Therefore, it is necessary to modify the resolution, use multi-source data as much as possible, and classify data according to the ice conditions. Referring to Beitsch"s idea of Antarctica partitioning and comparison, we further obtain the accuracy of remote sensing products under different ice conditions in a local region. We add China"s scientific research ship-based observation data to increase the sample numbers to research the Prydz Bay area, which covers rich surface ice types. The regional comparison provides a reference for understanding the limitations of PM SIC products in micro-area inversion and also guarantees ice prediction and navigation safety. Considering the rapid reduction of Antarctic sea ice in recent years and the appearance of a 40-year minimum Antarctic sea ice range in February 2022, It is imperative to develop high-precision real-time PM SIC products to find out the causes of sea ice anomalies and simulate sea ice changes in future. Knowing the inversion accuracy of various PM SIC products under different conditions will help to improve the subsequent PM SIC products and fusion algorithms. In the future, more factors that affect the accuracy of PM inversions, such as ice thickness, ice type, and other factors, should be considered to evaluate PM SIC products in other regions of the Antarctic in detail.