An optimization-based in-motion fine alignment and positioning algorithm for underwater vehicles

Fast and accurate in-motion alignment of strapdown inertial navigation system (SINS) is still a difficult problem in underwater missions. Conventional optimization-based alignment cannot isolate the inertial measurement unit (IMU) bias, and Kalman-based fine alignment converges slowly and requires accurately prior knowledge of the Doppler velocity logger (DVL)/SINS system. In this paper, a novel optimization-based fine alignment and posi-tioning algorithm is proposed using DVL measurements in which the IMU bias is considered, and the geodetic coordinate of SINS is updated by the displacement in the inertial frame. In addition, the sequence secondary planning algorithm is applied to the nonlinear optimization problem. Experimental results show that the position accuracy reaches 0.36% relative to the traveled distance, and the proposed method can improve the accuracy of alignment.

Automated summary

A novel optimization-based fine alignment and positioning algorithm is proposed using DVL measurements in underwater missions, which improves the accuracy of alignment significantly according to experimental results.