TY - JOUR
T1 - Nested Preanalyzed and Real-Time Corrected Matching Area Selection Method for Underwater Gravity-Aided Inertial Navigation
AU - Zhang, Zihan
AU - Wang, Bo
AU - Xiao, Wei
AU - Deng, Zhihong
AU - Fu, Mengyin
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - Gravity-aided inertial navigation system (GAINS) is an effective passive navigation method, which represents significant progress in underwater navigation. The matching area selection algorithm is one of the key techniques. Distinctive from conventional methods, in this article, a nested method for matching area selection is proposed, which establishes a joint observation of gravity anomalies at the current positions and auxiliary positions to obtain more abundant observational information. Comprehensively considering factors such as sensors, gravity anomaly map, and trajectory, etc., this method measures the matching capacity from a system perspective rather than the 2-D image characteristics, and quantitatively estimates the matching biases. The possible maneuvering navigation and other changes of trajectory and attitude angles are focused on, and a preanalysis and real-time correction method is designed accordingly. Experimental results show that the proposed method can select matching area more accurately and efficiently, and makes it easier to set the matching area selection criteria than conventional algorithms.
AB - Gravity-aided inertial navigation system (GAINS) is an effective passive navigation method, which represents significant progress in underwater navigation. The matching area selection algorithm is one of the key techniques. Distinctive from conventional methods, in this article, a nested method for matching area selection is proposed, which establishes a joint observation of gravity anomalies at the current positions and auxiliary positions to obtain more abundant observational information. Comprehensively considering factors such as sensors, gravity anomaly map, and trajectory, etc., this method measures the matching capacity from a system perspective rather than the 2-D image characteristics, and quantitatively estimates the matching biases. The possible maneuvering navigation and other changes of trajectory and attitude angles are focused on, and a preanalysis and real-time correction method is designed accordingly. Experimental results show that the proposed method can select matching area more accurately and efficiently, and makes it easier to set the matching area selection criteria than conventional algorithms.
KW - Gravity-aided inertial navigation system (GAINS)
KW - matching area
KW - nested method
KW - preanalysis and real-time correction
KW - sensors
UR - https://www.scopus.com/pages/publications/105039329283
U2 - 10.1109/JSEN.2026.3691705
DO - 10.1109/JSEN.2026.3691705
M3 - Article
AN - SCOPUS:105039329283
SN - 1530-437X
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
ER -