Coriolis mass flowmeter is one of the most widely used and fastest growing flowmeters. Digital signal processing technology is the core of Coriolis mass flowmeter and it directly determines the measurement accuracy, measurement stability and etc.. The mathematical model of sensor output signal is the basis of signal processing. Scholars at home and abroad have proposed many signal processing methods for Coriolis mass flowmeter. But there is a lack of comparison and evaluation for these signal processing methods based on different mathematical models and different applications. Therefore, the advantages and disadvantages of different signal processing methods are analyzed according to their feature extraction principles. The calculation accuracy, response rate, convergence, antijamming capability and sensitivity of different signal processing methods are compared and evaluated according to random walk model of single flow, mutant signal model of batch flow and ARMA signal model of gasliquid twophase flow. The optimized signal processing methods are determined for signal flow measurement, batch flow measurement and gasliquid twophase flow measurement to solve key technical issues.