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Performance of deeply integrated GPS/INS in dense forestry areas
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Andrey Soloviev
,
Charles Toth
Published/Copyright:
March 14, 2012
Abstract.
This paper demonstrates the performance of a deeply integrated GPS/inertial architecture under extreme canopy coverage, where traditional receiver technology fails to acquire and track GPS signals. GPS and inertial experimental data collected in various canopy coverage areas are applied to evaluate the system performance. Test results demonstrate that the deeply integrated approach enables reliable trajectory reconstruction capabilities and maintains sub-meter level of differential positioning precision for cases where the GPS signal is severely attenuated by the canopy.
Received: 2011-09-29
Accepted: 2012-01-10
Published Online: 2012-03-14
Published in Print: 2012-March
© 2012 by Walter de Gruyter Berlin Boston
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Articles in the same Issue
- Preface to the special issue on multi-sensor systems in engineering geodesy and navigation
- Performance of deeply integrated GPS/INS in dense forestry areas
- GNSS precise point positioning in regional reference frames using real-time broadcast corrections
- Measurement uncertainty in network RTK GNSS-based positioning of a terrestrial laser scanner
- Geo-referencing point clouds with transformational and positional uncertainties
- Indoor locating and inventory management based on RFID-Radar detecting data
- GNSS-based multi-sensor system for structural monitoring applications
Keywords for this article
GPS/INS;
deep integration;
navigation under dense canopy;
data quality monitoring
Articles in the same Issue
- Preface to the special issue on multi-sensor systems in engineering geodesy and navigation
- Performance of deeply integrated GPS/INS in dense forestry areas
- GNSS precise point positioning in regional reference frames using real-time broadcast corrections
- Measurement uncertainty in network RTK GNSS-based positioning of a terrestrial laser scanner
- Geo-referencing point clouds with transformational and positional uncertainties
- Indoor locating and inventory management based on RFID-Radar detecting data
- GNSS-based multi-sensor system for structural monitoring applications
