.png){kind=icon}
Return
Gravity Matching Algorithm Based on Backtracking for Small Range Adaptation Area
.png){kind=icon}
PRE
AI
DOI：10.1109/TIM.2024.3350139.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The existing gravity matching algorithms are affected either by gravity measurement error or by the initial position of inertial navigation system (INS). Filter algorithms can solve the problem under the condition of enough measurement data. However, the range of most adaptation areas is small. Due to the long matching period, the available measurement data may be not enough to make the filter converge. Aiming to obtain high-precision position information in the small range adaptation area, backtracking strategies that combine the filter algorithm are first proposed in this article. Next, the observability of gravity-aided navigation system is also analyzed based on graph analysis. Furthermore, the reverse error equations are obtained by analogy corresponding to the reverse solution, and the relationship between forward navigation and reverse navigation is also given. The results of simulation and marine experiment show that the proposed algorithm is superior to the existing gravity matching algorithms, and has a high positioning accuracy in the small range adaptation area.
Keywords:
Backtracking
Navigation
Gravity
Filtering algorithms
Underwater vehicles
Switches
Estimation
Backtracking navigation
gravity-aided inertial navigation system (GAINS)
reverse navigation
underwater navigation
Journal
IF:
5.9
Papers:
2.0W
Citations:
5.8W
Organization
Cited Papers
Special issue dedicated to William Fenical: a pioneer in marine/marine-derived microbial chemistry
OAAI
OAAIShareSaveImproved Particle Swarm Optimization Screening Iterative Algorithm in Gravity Matching Navigation.png)
IEEE SENSORS JOURNAL
IEEE SENSORS JOURNALIF4.5
PREAI
ShareSaveShareSaveShareSave
View more