The Quantification Method of Matching Capability of Areas in Gravity-Aided Inertial Navigation

Gravity-aided inertial navigation system (GAINS) is one of the essential research fields in underwater navigation technology, and one of the key problems to be solved is the selection of suitable matching areas. Distinctive from previous studies, the concept of Matching Capability of Areas (MCA) is...

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Bibliographic Details
Published in:IEEE sensors journal 2022-11, Vol.22 (21), p.1-1
Main Authors: Wang, Bo, Cai, Tijing, Fang, Ke
Format: Article
Language:English
Subjects:
Conditional probability
Digital mapping
Gravity
Gravity measurement
gravity-aided inertial navigation
Inertial navigation
Matching
matching capability of areas
Mathematical analysis
Navigation systems
Optimized production technology
Position errors
Sensors
suitable matching area
Trajectory
underwater navigation
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Summary:Gravity-aided inertial navigation system (GAINS) is one of the essential research fields in underwater navigation technology, and one of the key problems to be solved is the selection of suitable matching areas. Distinctive from previous studies, the concept of Matching Capability of Areas (MCA) is defined from the perspective of the whole system, not just the 2-D image characteristics. The key factors affecting the MCA are analyzed, including heading, matching length, INS initial position error, gravimeter error, map error, and INS drift. Taking these experimental conditions as a prior information, the method based on conditional probability to calculate the MCA is proposed, which can estimate the probability of matching within the required error limits in the given digital gravity map (DGM). After implementing a long-distance marine experiment, the validity of the MCA is verified and it is more comprehensive and effective than traditional characteristic parameters.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2022.3209341