A Polar Initial Alignment Algorithm for Unmanned Underwater Vehicles

Abstract

Due to its highly autonomy, the strapdown inertial navigation system (SINS) is widely used in unmanned underwater vehicles (UUV) navigation. Initial alignment is crucial because the initial alignment results will be used as the initial SINS value, which might affect the subsequent SINS results. Due to the rapid convergence of Earth meridians, there is a calculation overflow in conventional initial alignment algorithms, making conventional initial algorithms are invalid for polar UUV navigation. To overcome these problems, a polar initial alignment algorithm for UUV is proposed in this paper, which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame. By choosing the velocity and attitude as the measurement, the fine alignment with the Kalman filter (KF) is derived under the grid frame. Simulation and experiment are realized among polar, conventional and transversal initial alignment algorithms for polar UUV navigation. Results demonstrate that the proposed polar initial alignment algorithm can complete the initial alignment of UUV in the polar region rapidly and accurately.

Sensing and Connection Systems for Assisted and Autonomous Driving and Unmanned Vehicles

“…The issue of cooperative algorithms for unmanned aerial, underwater or ground vehicles (UAV/UUV/UGV) is addressed in half of the works that are published in the special issues [1,2,3,4,5,6], with the first four from Universities in China and the last two from South Korea and Spain. …”

“…[2,3,4], which are emerging as mobile sensor networks for the investigation and exploration of the underwater environment. Particularly, Ref.…”

“…To overcome these problems, a polar initial alignment algorithm for UUV is proposed in Ref. [4], which consists of coarse and fine alignment algorithms. Based on the principle of the conical slow drift of gravity, the coarse alignment algorithm is derived under the grid frame.…”

“…The proposed special issue has invited submissions related to sensing and connectivity systems for assisted and autonomous driving and for unmanned aerial, underwater and ground vehicles (namely UAV, UUV and UGV) [1,2,3,4,5,6,7,8,9,10,11,12]. Recent studies on the future of the automotive and robotic industry predict that the borders between the ICT (Information and Communication Technology) industry and the consumer industry will blur, and that vehicles will become consumer-centric [13].…”

Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method

“…The unmanned underwater vehicle (UUV), as an intelligent device for long-term remote underwater navigation, must carry a variety of sensors and special equipment for performing particular missions and tasks [ 1 , 2 , 3 ]. Among them, the forward-looking sonar in the UUV search and obstacle avoidance process has an unparalleled importance.…”