Imperial College London

DrCongLing

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Reader in Coding and Information Theory
 
 
 
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Contact

 

+44 (0)20 7594 6214c.ling

 
 
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Location

 

815Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Li:2019:10.1109/TSP.2019.2910480,
author = {Li, C and Gan, L and Ling, C},
doi = {10.1109/TSP.2019.2910480},
journal = {IEEE Transactions on Signal Processing},
pages = {2911--2922},
title = {Coprime sensing via Chinese remaindering over quadratic fields-part II: generalizations and applications},
url = {http://dx.doi.org/10.1109/TSP.2019.2910480},
volume = {67},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - The practical application of a new class of coprime arrays based on the Chinese remainder theorem (CRT) over quadratic fields is presented in this paper. The proposed CRT arrays are constructed by ideal lattices embedded from coprime quadratic integers with B 1 and B 2 being their matrix representations, respectively, whereby the degrees of freedom (DOF) surges toO(Idet(B 1 B 2 )I)with I det(B 1 )I + I det(B 2 )I sensors. The geometrical constructions and theoretical foundations were discussed in the accompanying paper in great detail, while this paper focuses on aspects of the application of the proposed arrays in two-dimensional (2-D) remote sensing. A generalization of CRT arrays based on two or more pairwise coprime ideal lattices is proposed with closed-form expressions on sensor locations, the total number of sensors, and the achievable DOF. The issues pertaining to the coprimality of any two quadratic integers are also addressed to explore all possible ideal lattices. Exploiting the symmetry of lattices, sensor reduction methods are discussed with the coarray remaining intact for economic maximization. In order to extend conventional angle estimation techniques based on uniformly distributed arrays to the method that can exploit any coarray configurations based on lattices, this paper introduces a hexagon-to-rectangular transformation to 2-D spatial smoothing, providing the possibility of finding more compact sensor arrays. Examples are provided to verify the feasibility of the proposed methods.
AU - Li,C
AU - Gan,L
AU - Ling,C
DO - 10.1109/TSP.2019.2910480
EP - 2922
PY - 2019///
SN - 1053-587X
SP - 2911
TI - Coprime sensing via Chinese remaindering over quadratic fields-part II: generalizations and applications
T2 - IEEE Transactions on Signal Processing
UR - http://dx.doi.org/10.1109/TSP.2019.2910480
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000466554400009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://ieeexplore.ieee.org/document/8686229
VL - 67
ER -