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Maximally economic sparse arrays and Cantor arrays

Liu, Chun-Lin and Vaidyanathan, P. P. (2017) Maximally economic sparse arrays and Cantor arrays. In: 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE , Piscataway, NJ, pp. 1-5. ISBN 978-1-5386-1251-4. https://resolver.caltech.edu/CaltechAUTHORS:20180419-082338809

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Abstract

Sparse arrays, where the sensors are properly placed with nonuniform spacing, are able to resolve more uncorrelated sources than sensors. This ability arises from the property that the difference coarray, defined as the differences between sensor locations, has many more consecutive integers (hole-free) than the number of sensors. In some implementations, it might be preferable that a) the arrays be symmetric, b) that the arrays be maximally economic, that is, each sensor be essential, and c) that the coarray be hole-free. The essentialness property of a sensor means that if it is deleted, then the difference coarray changes. Existing sparse arrays, such as minimum redundancy arrays (MRA), nested arrays, and coprime arrays do not satisfy these three criteria simultaneously. It will be shown in this paper that Cantor arrays meet all the desired properties mentioned above, based on a comprehensive study on the structure of the difference coarray. Even though Cantor arrays were previously proposed in fractal array design, their coarray properties have not been studied earlier. It will also be shown that the Cantor array has a hole-free difference coarray of size N^(log_2^3) ≈ N^(1.585) where N is the number of sensors. This is unlike the sizes of difference coarrays of the MRA, nested array, coprime array (all O(N^2)), and uniform linear arrays (O(N))^1.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/CAMSAP.2017.8313139DOIArticle
https://ieeexplore.ieee.org/document/8313139PublisherArticle
Additional Information:© 2017 IEEE. This work was supported in parts by the ONR grants N00014-15-1-2118 and N00014-17-1-2732, the NSF grant CCF-1712633, and the California Institute of Technology.
Funders:
Funding AgencyGrant Number
Office of Naval Research (ONR)N00014-15-1-2118
Office of Naval Research (ONR)N00014-17-1-2732
NSFCCF-1712633
CaltechUNSPECIFIED
Subject Keywords:Symmetric arrays, sparse arrays, hole-free difference coarrays, maximally economic arrays, Cantor arrays
Record Number:CaltechAUTHORS:20180419-082338809
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180419-082338809
Official Citation:C. L. Liu and P. P. Vaidyanathan, "Maximally economic sparse arrays and cantor arrays," 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Curacao, 2017, pp. 1-5. doi: 10.1109/CAMSAP.2017.8313139. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8313139&isnumber=8313053
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:85967
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:19 Apr 2018 16:09
Last Modified:03 Oct 2019 19:37

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