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Cited by 567

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Transmit beamforming for MIMO radar systems using signal cross-correlation

Fuhrmann, D.R., San Antonio, G.·2008·IEEE Transactions on Aerospace and Electronic Systems

Abstract

Proposed next-generation radar systems will have multiple transmit apertures with complete flexibility in the choice of the signals transmitted at each aperture. Here we propose the use of multiple signals with arbitrary cross-correlation matrix R, and show that R can be chosen to achieve or approximate a desired spatial transmit beampattern. Two specific problems are addressed. The first is the constrained optimization problem of finding the value of R which causes the true transmit beampattern to be close in some sense to a desired beampattern. This is approached using convex optimization techniques. The second is the problem of designing multiple constant-modulus waveforms with given cross-correlation R. The use of coded binary phase shift keyed (BPSK) waveforms is considered. A method for finding the code sequences based on random signaling with a structured correlation matrix is proposed. It is also shown that by restricting the class of admissible waveforms one reduces the set of possible signal correlation matrices.

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Metadata

Authors
Fuhrmann, D. R., & San Antonio, G.
Venue
IEEE Transactions on Aerospace and Electronic Systems
Published
2008-01
Volume
44
Issue
1
Pages
171-186
ISSN
0018-9251 (ISSN-L)
OpenAlex
W2129640939
Cited by
567
References
11
FWCI
46.48
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Transmit beamforming for MIMO radar systems using signal cross-correlation. https://app.cochat.ai/papers/10.1109/taes.2008.4516997
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Fuhrmann, D. R., & San Antonio, G. (2008). Transmit beamforming for MIMO radar systems using signal cross-correlation. IEEE Transactions on Aerospace and Electronic Systems. https://doi.org/10.1109/taes.2008.4516997

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.