GPS satellite and receiver instrumental biases estimation using SVD algorithm

The category I precision approach (CAT I PA) requirements can be achieved by augmenting the GPS. The space- based augmentation system (SBAS) in India is known as GPS aided geo augmented navigation (GAGAN). One of the prominent errors in GAGAN that limit the positional accuracy is instrumental bias....

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Veröffentlicht in:IEEE transactions on aerospace and electronic systems 2008-10, Vol.44 (4), p.1560-1566
Hauptverfasser: Sarma, A.D., Rao, G.S., Rao, P.V.D.S., Ramalingam, K.
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container_title IEEE transactions on aerospace and electronic systems
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creator Sarma, A.D.
Rao, G.S.
Rao, P.V.D.S.
Ramalingam, K.
description The category I precision approach (CAT I PA) requirements can be achieved by augmenting the GPS. The space- based augmentation system (SBAS) in India is known as GPS aided geo augmented navigation (GAGAN). One of the prominent errors in GAGAN that limit the positional accuracy is instrumental bias. The calibration of these biases is particularly important in achieving the CAT I PA landings. In this paper, singular value decomposition (SVD) based least mean square (LMS) algorithm is proposed to estimate the instrumental biases. The algorithm uses the values of one month period corresponding to three GAGAN stations. The experimental results indicate that the estimation precision of the satellite biases is of the order of plusmn0.6 ns. The estimated receiver bias for Hyderabad station using the proposed algorithm is -4.21 ns. The algorithm is validated with both fitted receiver bias method and hardware calibrated value. It is found that results are good and consistent over the observation period and confirm the validity of the developed algorithm.
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subjects Algorithms
Bias
Calibration
Clocks
Computer networks
Geographic information systems
Global Positioning System
Instruments
Least squares approximation
Receivers
Satellite broadcasting
Satellite navigation systems
Satellites
Singular value decomposition
Stations
Studies
title GPS satellite and receiver instrumental biases estimation using SVD algorithm
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