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" Enhanced detection of GNSS signals based on spatial combining "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 52562
Doc. No : TL22516
Call number : ‭MR44274‬
Main Entry : Mohammad Upal Mahfuz
Title & Author : Enhanced detection of GNSS signals based on spatial combining\ Mohammad Upal Mahfuz
College : University of Calgary (Canada)
Date : 2008
Degree : M.S.
student score : 2008
Page No : 155
Abstract : Weak and non-line of sight (NLOS) signals severely degrade the detection performance of Global Navigation Satellite Systems (GNSS) signals. High attenuation and severe multipath introduces a challenge in the detectability of GNSS signal indoors. The use of antenna arrays in GNSS allows for the provision that multiple spatially separated antennas receive uncorrelated signal fading independent of each other. Being quite common in point-to-point wireless communications, the concept of antenna array in GNSS is considered as a new application. The independent fading statistics are used to reduce noise and to increase signal to noise ratio (SNR) at the receiver, which ultimately increases the detectability of the signals in any environment. This research discusses the enhanced detection of GNSS signals based on spatial combining of multiple antenna outputs. From spatially apart multiple antenna receivers, there is a possible diversity gain when the individual antenna outputs are combined in an appropriate fashion. For two antennas, the diversity gain is in the range of 4 to 5 dB relative to a single antenna. The theory of multiple signals combining along with the experimental setup to demonstrate the approach with real GPS data is presented. The data presented supports the fact there is significant gain in signal to noise ratio (SNR) which improves the detection of GNSS signals in degraded signal environments, e.g. indoors. A deeper investigation on the spatial correlation of GPS L1 multiple receiver channels shows that the data collaborates the theory and, above all the spatial diversity method enhances detection in a statistically significant manner.
Subject : Applied sciences; Aerospace engineering; Electrical engineering; 0544:Electrical engineering; 0538:Aerospace engineering
Added Entry : University of Calgary (Canada)
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