The problem of optimum sparse array configuration to maximize the beamformer output signal-to-interference plus noise ratio (MaxSINR) in the presence of multiple sources of interest (SOI) has been recently addressed in the literature. In this paper, we consider a shared aperture system where
optimum sparse subarrays are allocated to individual SOIs and collectively span the entire full array receiver aperture. Each
subarray may have its own antenna type and can comprise a different number of antennas. The optimum joint sparse subarray design for shared aperture based on maximizing the
sum of the subarray beamformer SINRs is considered with and without SINR threshold constraints. We utilize Taylor series approximation and sequential convex programming (SCP) techniques to render the initial non-convex optimization a convex
problem. The simulation results validate the shared aperture design solutions for MaxSINR for both cases where the number of sparse subarray antennas is predefined or left to comstitute an optimization variable.
Funding
The work of A. Deligiannis and S. Lambotharan was supported by the Engineering and Physical Sciences Research Council (EPSRC) Grant number
EP/K014307/1 and the MOD University Defence Research Collaboration (UDRC) in Signal Processing. The work of Dr. Amin was supported by NSF grant no. 1547420 and by the 2017 Fulbright Scholarship program
History
School
Mechanical, Electrical and Manufacturing Engineering
Published in
IEEE Transactions on Aerospace and Electronic Systems
Volume
55
Issue
2
Pages
939 - 950
Citation
DELIGIANNIS, A. ... et al, 2018. Optimum sparse subarray design for multitask receivers. IEEE Transactions on Aerospace and Electronic Systems, 55 (2), pp.939-950.
Publisher
Institute of Electrical and Electronics Engineers
Version
NA (Not Applicable or Unknown)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 3.0 (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/
Acceptance date
2018-07-28
Publication date
2018-08-27
Notes
This paper was published by IEEE as Open Access. It is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/.