In view of the problem in analysis and quantitative description on MEMS gyroscope noise based on common Allan variance, dynamic Allan variance for MEMS gyro output signal analysis is proposed and improved. According to the principle of dynamic Allan variance, dynamic identification of the error coefficient has been achieved, the error variation laws with time are obtained. The estimation of various kinds of noise by using the least square fitting method has problems that individual error coefficient is negative. Therefore, Nelder Mead simplex method is used in the nonlinear curve fitting of variance. Test results show that the improved method can accurately describe the data noise value, moreover, signal frequency stability and changing characteristics of the error term are reflected.