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Title: Differential positioning using signals of opportunity
Author: Webb, T. A.
Awarding Body: University College London (University of London)
Current Institution: University College London (University of London)
Date of Award: 2013
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Global Navigation Satellite Systems (GNSS) have become the positioning systems of choice for many applications. However, GNSS signals are susceptible to obstruction, interference and jamming. As a result, alternative technologies that can backup and operate independently of GNSS are required. One option is to use signals of opportunity, which are signals not designed or modi- ed speci cally for positioning. A key bene t is cost as there is no need to install and maintain additional transmission infrastructure. Furthermore, signals of opportunity have the extensive coverage and penetration necessary to reach di cult environments. The proposed positioning technique operates by comparing signals received at a user location with those received at a reference, or other user location. Signals are brought together and correlation-tested to obtain differential ranging measurements which are processed to yield the user's position. Hardware and signal processing solutions necessary to position with signals of opportunity are explored. The technology is validated on AM broadcast transmissions in the low frequency (LF) and medium frequency (MF) bands. Using these transmissions, results indicate that a positioning solution can be obtained in GNSS compromised environments, such as indoors and in urban canyons. In principle, the technique can be adapted to operate on different kinds of signals regardless of their modulation and content - so long as they can be separated from their counterparts. As a consequence of this, the concepts may be applied to other kinds of transmissions, with the potential of developing a system that achieves enhanced performance by exploiting heterogeneous transmissions from different parts of the spectrum.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available