Optimum Sparse Array Design for Multiple Beamformers with Common Receiver

Wang, Xiangrong; Amin, Moeness G.; Wang, Xianghua

doi:10.1109/icassp.2018.8461355

Cited by 13 publications

(3 citation statements)

References 28 publications

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“…Here, means the element-wise product, c and r are two auxiliary binary selection vectors, P i ∈ {0, 1} 2M N in (12b) is the transmission selection matrix, which is used to select the real and imaginary parts of the N weights corresponding to the ith transmitter, as shown in (13). Eqs.…”

Section: A Group Sparse Solutions Through Scamentioning

confidence: 99%

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

Hamza¹,

Zhai²,

Wang³

et al. 2021

Preprint

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Sparse array design aided by emerging fast sensor switching technologies can lower the overall system overhead by reducing the number of expensive transceiver chains. In this paper, we examine the active sparse array design enabling the maximum signal to interference plus noise ratio (MaxS-INR) beamforming at the MIMO radar receiver. The proposed approach entails an entwined design, i.e., jointly selecting the optimum transmit and receive sensor locations for accomplishing MaxSINR receive beamforming. Specifically, we consider a colocated multiple-input multiple-output (MIMO) radar platform with orthogonal transmitted waveforms, and examine antenna selections at the transmit and receive arrays. The optimum active sparse array transceiver design problem is formulated as successive convex approximation (SCA) alongside the twodimensional group sparsity promoting regularization. Several examples are provided to demonstrate the effectiveness of the proposed approach in utilizing the given transmit/receive array aperture and degrees of freedom for achieving MaxSINR beamforming.

show abstract

Section: A Group Sparse Solutions Through Scamentioning

confidence: 99%

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

Hamza¹,

Zhai²,

Wang³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Environment-dependent sparse receive beamformer striving to achieve MaxSINR can potentially provide sparse configurations that improve target detection and estimation accuracy [13]- [21]. In this paper, we consider MaxSINR receive beamformer design for MIMO radar operation.…”

Section: Introductionmentioning

confidence: 99%

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

Hamza

Zhai

Wang

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

View full text Add to dashboard Cite

Sparse array design aided by emerging fast sensor switching technologies can lower the overall system overhead by reducing the number of expensive transceiver chains. In this paper, we examine the active sparse array design enabling the maximum signal to interference plus noise ratio (MaxSIN-R) beamforming at the MIMO radar receiver. The proposed approach entails an entwined design, i.e., jointly selecting the optimum transmit and receive sensor locations for accomplishing MaxSINR receive beamforming. Specifically, we consider a colocated multiple-input multiple-output (MIMO) radar platform with orthogonal transmitted waveforms, and examine antenna selections at the transmit and receive arrays. The optimum active sparse array transceiver design problem is formulated as successive convex approximation (SCA) alongside the twodimensional group sparsity promoting regularization. Several examples are provided to demonstrate the effectiveness of the proposed approach in utilizing the given transmit/receive array aperture and degrees of freedom for achieving MaxSINR beamforming.

show abstract

“…In this case, optimum sparse array is the one that achieves and maintains performance optimality under various sensing conditions using a given and limited number of sensors within the available aperture. One of key optimality criteria is maximizing the signal-to-interference plus noise ratio (SINR) which has been quite successful in yielding array configurations resulting in enhanced target parameter estimation accuracy [5]- [8].…”

Section: Introductionmentioning

confidence: 99%

Sparse Array DFT Beamformers for Wideband Sources

Hamza¹,

Amin²

2019

2019 IEEE Radar Conference (RadarConf)

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Sparse arrays are popular for performance optimization while keeping the hardware and computational costs down. In this paper, we consider sparse arrays design method for wideband source operating in a wideband jamming environment. Maximizing the signal-to-interference plus noise ratio (MaxSINR) is adopted as an optimization objective for wideband beamforming. Sparse array design problem is formulated in the DFT domain to process the source as parallel narrowband sources. The problem is formulated as quadratically constraint quadratic program (QCQP) alongside the weighted mixed l1−∞norm squared penalization of the beamformer weight vector. The semidefinite relaxation (SDR) of QCQP promotes sparse solutions by iteratively re-weighting beamformer based on previous iteration. It is shown that the DFT approach reduces the computational cost considerably as compared to the delay line approach, while efficiently utilizing the degrees of freedom to harness the maximum output SINR offered by the given array aperture.

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Optimum Sparse Array Design for Multiple Beamformers with Common Receiver

Cited by 13 publications

References 28 publications

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

Sparse Array Transceiver Design for Enhanced Adaptive Beamforming in MIMO Radar

Sparse Array DFT Beamformers for Wideband Sources

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