The sensor structure and measurement circuit of electronic analytical balances are complex and cannot accurately calculate the transfer function of the system. In order to estimate the transfer function of the system and improve the signal-to-noise ratio of the measurement data, the order of the transfer function of the system is estimated by the method of Laplace transform, the equation of state of the system under steady state is derived, and the method of estimating the system parameters by autoregressive method and combining with Kalman filtering is proposed to filter the measurement data. Through the experimental estimation of equation parameters and noise intensity from offline data, the filtered data verify the smoothness of the process, and the significant level is as low as 0. 001. Compared with the commonly used sliding window filtering method, the smoothness and stability of the new method are significantly improved, the measurement standard deviation is 30% of the original method, the linearity can reach 6. 7×10 -5 , and the response time is as low as 10%. The experimental data of four samples verify the feasibility and effectiveness of the proposed method.