Abstract
The geomagnetic matching aided positioning system based on Iterative Closest Contour Point (ICCP) algorithm can suppress the accumulation error of the inertial navigation system and achieve the accurate positioning of the vehicle. Aiming at the problem that the ICCP algorithm is sensitive to heading error and easily mismatches in regions with similar geomagnetic general features, an improved ICCP matching algorithm based on geomagnetic vector is proposed. The ant colony algorithm is designed to improve the search strategy in a large probability range. The geomagnetic three-dimensional vector feature and the Hausdoff distance are employed as the objective function for multiple iterations, improving matching efficiency and accuracy. Simulation results show that compared with the traditional ICCP algorithm, the positioning error of the matching track, the heading error, and the matching time of the improved ICCP algorithm are reduced by 69.6%, 44.0% and 39.0%, respectively.
Highlights
The autonomous navigation with long-endurance and high-precision are key performance parameters for Autonomous Underwater Vehicles (AUV)
In this article [4], in order to avoid the influence of time-varying noise and weak illumination on slam, the author proposes a magnetic gradient-aided navigation method based on adaptive slam
The Iterative Closest Contour Point (ICCP) matching algorithm is derived from the Iterative Closest Point (ICP) for image matching
Summary
The autonomous navigation with long-endurance and high-precision are key performance parameters for Autonomous Underwater Vehicles (AUV). In this article [6], the author adopts a new processing and analysis method for 3D multibeam sonar data, which has high real-time, good effect and strong readability, and improves the accuracy and efficiency of comparative navigation. The improvement of vector features can solve the mismatch problem of the geomagnetic matching algorithm in areas with similar total geomagnetic features and enhance the positioning accuracy [10]. In order to improve the mismatching phenomenon of the algorithm in the area where the total geomagnetic intensity feature does not change significantly, combined with the vector characteristics of the geomagnetic field, the three-component geomagnetic intensity is used to improve the objective function of the matching algorithm, which more fully and comprehensively describes the similarity in the matching process, which greatly reduces the position error and heading error of the matching result, and effectively improves the matching efficiency and accuracy of the algorithm
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
