Novel Dictionary Decomposition to Acquire GPS Signals Using Compressed Sensing

Albu-Rghaif, Ali and Lami, Ihsan (2014) Novel Dictionary Decomposition to Acquire GPS Signals Using Compressed Sensing. In: 2014 World Congress on Computer Applications and Information Systems (WCCAIS), 17 - 19 Jan 2014, Hammamet, Tunisia.

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Abstract

When acquiring any wireless signal such as GPS, there is a strong association between the amount of integration, correlation or matching performed by the receiver with the strength of the signal, depending on the acquisition technique used. The Compressive Sensing technique (CS) does reduce the computation by up to 60% over correlators based method, yet still maintains acquisition integrity. This paper proposes a new method for implementing the dictionary matrix required for CS and achieving a further saving of more than 80% in the signal acquisition process without loss of the integration between the code and frequency irrespective of the signal strength. This is achieved by removing the generated Doppler shifts from the “overcomplete” dictionary matrix, while keeping the carrier frequency fixed for all these generated shifted SV codes. Our MATLAB simulation for various signal condition scenarios proves that up to 90% of computational complexity and memory space can saved.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2014 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: dictionary decomposition; GPS signal acquisition; compressive sensing
Subjects: Q Science > Q Science (General)
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 14:30
Last Modified: 01 Sep 2016 13:55
URI: http://bear.buckingham.ac.uk/id/eprint/58

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