Optimization-based alignment for inertial navigation systems: Theory and algorithm

Inertial navigation system (INS) necessitates an alignment stage to determine the initial attitude at the very start. A novel alignment approach is devised by way of an optimization method, in contrast to the existing alignment methods, e.g., gyrocompassing and filtering techniques. This paper shows...

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Vydané v:Aerospace science and technology Ročník 15; číslo 1; s. 1 - 17
Hlavní autori: Wu, Meiping, Wu, Yuanxin, Hu, Xiaoping, Hu, Dewen
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Issy-les-Moulineaux Elsevier SAS 01.01.2011
Elsevier
Predmet:
Algorithms
Alignment
Applied sciences
Computer science; control theory; systems
Control theory. Systems
Detection, estimation, filtering, equalization, prediction
Eigenvector
Exact sciences and technology
Filtering
Global observability
Inertial navigation
Inertial navigation system
Information, signal and communications theory
Mathematical analysis
Optimization
Sensitivity analysis
Sensors
Signal and communications theory
Signal, noise
System theory
Telecommunications and information theory
Alignment
Global observability
Eigenvector
Inertial navigation system
Euler equation
Navigation system
Sensitivity analysis
Filtering
Translation motion
Systems theory
Algorithm
Optimization
Accuracy
Simulation
Inertial navigation
Position measurement
Robustness
Observability
ISSN:1270-9638, 1626-3219
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Popis
Shrnutí:Inertial navigation system (INS) necessitates an alignment stage to determine the initial attitude at the very start. A novel alignment approach is devised by way of an optimization method, in contrast to the existing alignment methods, e.g., gyrocompassing and filtering techniques. This paper shows that the INS attitude alignment can be equivalently transformed into a “continuous” attitude determination problem using infinite vector observations. It reveals an interesting link between these two individual problems that has been studied in parallel for several decades. The INS alignment is heuristically established as an optimization problem of finding the minimum eigenvector. Sensitivity analysis with respect to sensor biases is made and explicit error equations are obtained for a special stationary case. Simulation studies and experiment tests favorably demonstrate its rapidness, accuracy and robustness. The proposed approach is inherently able to cope with any large angular motions, as well as high-frequency translational motions. By inspecting the constant initial Euler angles, it could alternatively be used to detect the existence of significant sensor biases.
Bibliografia:ObjectType-Article-2
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content type line 23
ISSN:1270-9638
1626-3219
DOI:10.1016/j.ast.2010.05.004