MIMO Radar Beampattern Design via Algorithm Unrolling

Optimizing a transmit multiple-input–multiple-output (MIMO) radar waveform subject to the nonconvex constant modulus constraint (CMC) remains a problem of enduring interest. The past decade has seen a variety of tailored iterative approaches with various performance–complexity tradeoffs. Despite pro...

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Veröffentlicht in:	IEEE transactions on aerospace and electronic systems Jg. 60; H. 6; S. 9204 - 9220
Hauptverfasser:	Metwaly, Kareem, Kweon, Junho, Alhujaili, Khaled, Gini, Fulvio, Greco, Maria Sabrina, Rangaswamy, Muralidhar, Monga, Vishal
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.12.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aerospace and electronic systems Algorithm unrolling Algorithms constant modulus Deep learning deep learning (DL) Design optimization Interference Iterative algorithms Iterative methods Machine learning MIMO radar multiple-input multiple-output (MIMO) radar Neural networks Parameters Radar Signal to noise ratio Tradeoffs Training waveform design Waveforms
ISSN:	0018-9251, 1557-9603
Online-Zugang:	Volltext
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