This paper proposed a self-calibration algorithm for triaxial accelerometer. By analyzing the measurement error factors, the parametric model of accelerometer output was built. According to the principle that the modulus value of gravity vector at a fixed point is constant, the nonlinear state space model of calibration parameters was derived. Further, the iterated extended kalman filter was used to avoid the problem of high space complexity of off-line calibration algorithm. Through numerical simulation the efficiency of the proposed IEKF algorithm was illustrated. Simulation results also demonstrated the superior performance of iterated extended kalman filter over the Least squares algorithm in the application of accelerometer calibration.