DCSR : a dynamic channel and resolution sampling for a compressive sensing receiver to acquire GPS signals

Albu-Rghaif, Ali and Lami, Ihsan (2013) DCSR : a dynamic channel and resolution sampling for a compressive sensing receiver to acquire GPS signals. In: 2013 IEEE International Conference on Microwaves, Communications, Antennas and Electronics Systems (COMCAS), 21 - 23 Oct 2013, Tel Aviv, Israel.

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Abstract

The use of Compressive Sensing (CS) technique to acquire GPS signals saves processing time when compared with software FFT based receivers. The computational complexity is reduced by up to 60%. Such CS solution uses a fixed size measurement matrix chosen to offer a compromise between the processing overhead and signals acquisition success level. This paper proposes a dynamic acquisition algorithm for GPS signals based on CS. Instead of using a fixed size sampling channels and fixed correlators in the measurement matrix, our DSCR dynamically changes the number and size of the required Channels/Correlators according to the received GPS signals power during acquisition. This adaptive solution offers better fix capability when the GPS receiver is located in harsh signal environment or it will save valuable processing/decoding time (battery power, especially for Smartphones) when the receiver outdoors. A feedback loop is devised to control the sampling channels number and resize the measurement matrix.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: GPS signal; dynamic acquisition; sub-Nyquist sampling; compressive sensing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Divisions: School of Science > Applied Computing
Depositing User: Ihsan Lami
Date Deposited: 18 Aug 2015 14:28
Last Modified: 01 Sep 2016 12:23
URI: http://bear.buckingham.ac.uk/id/eprint/56

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