Title
Ins Stochastic Error Detection During Kinematic Tests And Impacts On Ins/Gnss Performance
Abstract
Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) integration requires accurate modelling of both INS deterministic and stochastic errors. The Allan Variance (AV) analysis on INS static data is one method of determining INS stochastic errors. However, it is known that INS errors can vary depending on a vehicle's motion and environment, and application of AV results from static data in kinematic operations typically results in an over-confident estimation of stochastic. In order to overcome this limitation, this paper proposes the use of Dynamic Allan Variance (DAV). The paper compares the resulting performance of the INS/GNSS integrated system by varying the stochastic coefficients obtained from the AV and DAV. The results show that the performance improved when utilizing the stochastic coefficients obtained from the DAV, applied on a kinematic dataset compared to the AV, applied on a static laboratory dataset.
Year
DOI
Venue
2013
10.1080/10095020.2013.817108
GEO-SPATIAL INFORMATION SCIENCE
Keywords
Field
DocType
inertial sensor, dynamic Allan variance, INS stochastic error, INS dynamic dependent error
Inertial navigation system,Kinematics,GPS/INS,Satellite system,Real-time computing,Artificial intelligence,GNSS applications,Allan variance,Computer vision,Static data,Simulation,Error detection and correction,Mathematics
Journal
Volume
Issue
ISSN
16
3
1009-5020
Citations 
PageRank 
References 
0
0.34
1
Authors
3
Name
Order
Citations
PageRank
Azmir Hasnur-Rabiain111.07
Allison Kealy27012.14
Mark R. Morelande319524.96