Huan, M. orcid.org/0000-0003-3926-2748, Liang, J. orcid.org/0000-0003-3306-2294, Wu, Y. et al. (2 more authors) (2023) SASA: Super-resolution and ambiguity-free sparse array geometry optimization with aperture size constraints for MIMO radar. IEEE Transactions on Antennas and Propagation. ISSN 0018-926X
Abstract
To improve the performance of multiple-input-multiple-output (MIMO) radar, various sparse arrays have been employed. However, the angular resolution of existing non-uniform arrays optimized by either combinatorial algorithms or heuristic ones is limited by the Rayleigh criterion, which is strictly related to the aperture size. Based on the angular ambiguity function (AAF) analysis, two new models are established in this work for directly optimizing the sidelobe level (SLL) or the main lobe width (MLW) with the constraints of aperture size and element spacing. The aforementioned designs result in non-convex and nonlinear optimization problems, and solutions are derived via the alternating direction multiplier method (ADMM). Furthermore, considering a parametric trade-off between SLL and MLW, a hybrid algorithm is proposed to search for the SLL-MLW Pareto front boundary. Finally, simulations are provided to demonstrate the high angular resolution and ambiguity-free properties of the optimized sparse arrays.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | MIMO radar; sparse array; angular ambiguity function; non-convex optimization , angular resolution |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 31 Mar 2023 15:49 |
Last Modified: | 30 Mar 2024 01:13 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/tap.2023.3262157 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197914 |