Multi-Aircraft Inertial Navigation Data Fusion Method Aided by One Pseudolite
Pseudolite aided all parameters weighted least squares (PAAPWLS) data fusion method is proposed to improve multi-aircraft inertial positioning accuracy. The data fusion system was mainly composed of the inter-flight data link, inertial navigation system (INS) and one pseudolite. The data link performed two functions: real-time communication and mutual ranging between aircrafts. INS provided position data. The pseudolite receiver outputted distances between aircrafts and the pseudolite. The PAAPWLS algorithm was applied to data fusion in order to estimate the multi-aircraft inertial position errors when the aircrafts fly across the pseudolite. Simulation results show that the method works effectively and the position error can be improved to less than 40m (1σ) with the help of the method.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784412442
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Supplemental Notes:
- © 2012 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Liu, Jun-Cheng
- Zhang, Jing-Juan
- Tan, Li-Fen
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Conference:
- Twelfth COTA International Conference of Transportation Professionals
- Location: Beijing , China
- Date: 2012-8-3 to 2012-8-6
- Publication Date: 2012-8
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 932-940
- Monograph Title: CICTP 2012: Multimodal Transportation Systems—Convenient, Safe, Cost-Effective, Efficient
Subject/Index Terms
- TRT Terms: Air traffic control; Aircraft; Data fusion; Dead reckoning; Inertial navigation systems; Position fixing
- Uncontrolled Terms: Pseudolites
- Subject Areas: Aviation; Data and Information Technology; Operations and Traffic Management; I73: Traffic Control;
Filing Info
- Accession Number: 01500612
- Record Type: Publication
- ISBN: 9780784412442
- Files: TRIS, ASCE
- Created Date: Nov 12 2013 2:35PM