In the measurement process of thermal mass flowmeter, due to the systematic error of analog -to-digital converter (ADC) itself, and the influence of input signal and external circuit noise, the digital quantity signal transformed by ADC will deviate from the theoretical value and constantly fluctuate. Therefore, we propose a software filtering method based on the improved Kalman algorithm, which can improve the convergence speed of kalman algorithm while eliminating the error. In addition, the probability distribution model of data error is established by probability statistics method, which provides theoretical basis for kalman parameter selection. Finally, the algorithm is implemented on FPGA and verified by experiments. Compared with the data before filtering, the average error is reduced from 1.81% to 0.82%, and the data fluctuation is less than 2LSB.The results show that the method can effectively eliminate errors and improve the stability of the measurement system.[ 基金项目：国家自然科学基金资助项目（12074354）]