 On the GPS/IMU sensors’ noise estimation for enhanced navigation integrityMamoun F. Abdel-Hafez Mathematics and Computers in Simulation (MATCOM), 2012, vol. 86, issue C, 101-117 Abstract: In this paper, the problem of estimating the measurements’ noise statistics of the Global Positioning System (GPS) is addressed. First, a model matching technique is used to estimate the GPS measurements’ noise statistics. Then, the formulation of the measurements and process noise estimation using the Autocovariance Least Squares technique will be derived for the time-varying GPS/IMU system. It is assumed that the process noise covariance matrix is known or determined a priori through off-line calibration. The Autocovariance Least Squares method improves on the assumptions of the model matching technique by considering the time-correlation in the measurements’ residual sequence due to the a priori unknown GPS measurements’ noise covariance matrix. Both methods make use of statistical sampling theory in the estimation filter. Simulation results for both methods will be presented at the end of the paper. The results are compared and the improvement gained when using the Autocovariance Least Squares method in comparison to the model matching technique will be shown. Keywords: GPS; IMU; Noise estimation; Statistical estimation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:86:y:2012:i:c:p:101-117 DOI: 10.1016/j.matcom.2010.03.005 Access Statistics for this article Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier |
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