Sparse Arrays and Sampling for Interference Mitigation and DOA Estimation in GNSS

This paper establishes the role of sparse arrays and sparse sampling in antijam global navigation satellite systems (GNSS). We show that both jammer direction of arrival estimation methods and mitigation techniques benefit from the design flexibility of sparse arrays and their extended virtual apert...

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Bibliographic Details
Published in:Proceedings of the IEEE Vol. 104; no. 6; pp. 1302 - 1317
Main Authors: Amin, Moeness G., Wang, Xiangrong, Zhang, Yimin D., Ahmad, Fauzia, Aboutanios, Elias
Format: Journal Article
Language:English
Published: New York IEEE 01.06.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Antenna arrays
Antennas
Antijam
Arrays
Direction-of-arrival estimation
DOA estimation
Global navigation satellite system
global navigation satellite systems (GNSS)
GNSS
Interference
interference mitigation
Jammers
Jamming
Receivers
Reconstruction
Sampling
Satellite navigation systems
Signatures
sparse arrays
Sparsity
DOA estimation
global navigation satellite systems (GNSS)
Antijam
sparse arrays
interference mitigation
ISSN:0018-9219, 1558-2256
Online Access:Get full text
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Summary:This paper establishes the role of sparse arrays and sparse sampling in antijam global navigation satellite systems (GNSS). We show that both jammer direction of arrival estimation methods and mitigation techniques benefit from the design flexibility of sparse arrays and their extended virtual apertures or coarrays. Taking advantage of information redundancy, significant reduction in hardware and computational cost materializes when selecting a subset of array antennas without sacrificing jammer nulling or localization capabilities. In addition to the spatial array sparsity, antijam can utilize sparsity of jammers in the spatio-temporal frequency domains. By virtue of their finite number, jammers in the field of view are sparse in the azimuth and elevation directions. For the class of frequency modulated jammers, sparsity is also exhibited in the joint time-frequency signal representation. These spatial and signal characteristics have called for the development of sparsity-aware antijam techniques for the accurate estimation of jammer space-time-frequency signature, enabling its effective sensing and excision. Both theory and simulation examples demonstrate the utility of coarrays, sparse reconstructions, and antenna selection techniques for antijam GNSS.
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ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2016.2531582