The error model of strap-down inertial navigation system（SINS）initial alignment is nonlinear under large azimuth misalignment angle condition

and it can be processed using particle filtering（PF）algorithm.Aiming at the problem that importance density function of standard particle filtering algorithm is difficult to select

a new algorithm of iterated cubature particle filtering（ICPF）is proposed.Gauss-Newton iteration and cubature Kalman filtering（CKF）algorithm are combined to obtain iterated CKF（ICKF）algorithm.The latest measurement information are used in this algorithm to improve the innovation variance and covariance in iterative process

and obtain higher estimation precision.The importance density function of PF is obtained by ICKF algorithm and particle degradation phenomenon is effectively restrained.Simulation and experimental results show that

the filtering precision of this algorithm is higher than standard PF and CPF algorithm and it is a very effective nonlinear filtering algorithm.