Transmit beamforming for MIMO radar systems using signal cross-correlation

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

572 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/038f4e8f1bb1c1365d2acd212a71b47fa8c23db3

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In Aerospace Engineering

Citations in the corpus

On Probing Signal Design For MIMO Radar (2006, methodology): “…with location is given by (4) where is the covariance matrix of , i.e., (5) 1053-587X/$25.00 © 2007 IEEE The “spatial spectrum” in (4), as a function of , will be called the transmit beampattern (a more detailed derivation of, and further discussions on, (1)–(5) above can be found in [3], [8]).”
Simultaneous radar and communications emissions from a common aperture, Part I: Theory (2017, background): “This arrangement is a form of MIMO beampattern design [21]–[25] with the particular requirement that the individual waveforms be physically realizable by a high-power transmitter; i.”
Designing Unimodular Sequence Sets With Good Correlations—Including an Application to MIMO Radar (2009, unknown): “In [11] and [12] the covariance matrix of the transmitted waveforms is optimized to achieve a given transmit beampattern, while in [13] the waveforms are designed directly to approximate a given covariance matrix.”
Secure Radar-Communication Systems With Malicious Targets: Integrating Radar, Communications and Jamming Functionalities (2019, methodology): “Note that an ideal radar beampattern should be obtained before designing the beamforming and artificial noise, which can be generated by solving the following constrained least-squares (LS) problem [9], [43] as an example”
Signal Synthesis and Receiver Design for MIMO Radar Imaging (2008, background): “However, enforcing orthogonality among the transmitted waveforms as well as requiring such good autocorrelation properties at the signal generation phase significantly complicates the waveform synthesis problem.”
MIMO Radar Waveform Design With Constant Modulus and Similarity Constraints (2014, methodology): “In [6], the covariance matrix was devised to achieve or approximate a desired spatial beam pattern; also introduced there was amethod to synthesize constant modulus waveforms for a given covariance matrix.”
MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission (2017, methodology): “In [34], a constrained least-square problem is formulated to approach an ideal beampattern.”
Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar (2019, methodology): “To this aim, we use the loss function proposed in [50], [54] to evaluate the radar performance, which is the weighted sum of two parts: beam pattern error and cross correlation.”
Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design (2017, methodology): “We refer readers to [41]–[43] for more details on this topic.”
MIMO Radar Using Compressive Sampling (2009, unknown): “beampattern by transmitting correlated waveforms [7]–[9].”
MIMO Radar Waveform Optimization With Prior Information of the Extended Target and Clutter (2009, background): “In [5] and [6], the covariance matrix of the transmitted waveforms is designed such that the power can be transmitted to a desired range of angles.”