An Optimal Indirect In-Motion Coarse Alignment Method for GNSS-Aided SINS

Aiming at the problems of low precision and poor adaptability of traditional in-motion coarse alignment methods for vehicle strapdown inertial navigation system (SINS), an optimal indirect in-motion coarse alignment method aided by global navigation satellite system (GNSS) is proposed. The attitude matrix problem is transformed into Wahba problem to make full use of the observation vectors information. In the process of observation vectors construction, the integral interval of the observation vectors is shortened by the sliding interval method to weaken the accumulation of constant error of inertial devices. The Wahba problem is solved by singular value decomposition (SVD) algorithm. Combined with the output information of GNSS and SINS, the equivalent rotation vector and constant bias of gyroscope are used as state variables to construct the process model and measurement model. The type-2 fuzzy adaptive Kalman filter algorithm is proposed to solve the problem of inaccurate measurement noise in the process of state variables estimation, and the transform matrix of carrier frame is continuously modified to obtain a more accurate attitude conversion matrix. Digital simulation and vehicle experiments show that the proposed algorithm can significantly improve the alignment accuracy of inertial navigation system on moving base.