A Characteristic Parameter Matching Algorithm for Gravity-Aided Navigation of Underwater Vehicles

• Published in: IEEE transactions on industrial electronics (1982) Vol. 66; no. 2; pp. 1203 - 1212
• Main Authors: Wang, Bo, Zhu, Jingwei, Deng, Zhihong, Fu, Mengyin
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-02-2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Approximation algorithms; Computer simulation; Error correction; Gravitational fields; Gravity; Gravity anomalies; Gravity-aided navigation; Inertial navigation; Matching; matching algorithm; Mathematical analysis; Navigation systems; Parameters; Particle filters; Position measurement; Trajectories; Trajectory; Underwater vehicles
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2018.2831171

The gravity matching algorithm is a key of the gravity-aided inertial navigation system (INS). The traditional matching algorithm connects only the measured gravity anomaly data to the position of the carrier according to a certain method to correct the inertial error. The gravitational field characteristic parameters should also be considered in the matching algorithm to improve the matching accuracy and reduce the number of mismatching. Therefore, based on the vector matching algorithm, a characteristic parameter matching algorithm is proposed. This paper presents new methods to calculate the characteristic parameters and the range of particle filters to increase the accuracy of matching. The gravity anomaly value of each particle is calculated more accurately by the proposed method of continuous gravity anomaly. Due to the high short-time accuracy of inertial navigation, the final trajectory is obtained by rigid transformation of a series of positions indicated by the INS corresponding to the trajectory. Simulation results prove that when compared with the vector matching algorithm, the proposed method makes the matching results more accurate and more reliable.