Generalized Widely Linear Robust Adaptive Beamforming: A Sparse Reconstruction Perspective

Yue, Yaxing; Zhang, Zongyu; Shi, Zhiguo

doi:10.1109/taes.2024.3397240

Cited by 3 publications

References 37 publications

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Effects of Mutual Coupling for Bistatic Airborne Radar with End-fire Array in Clutter Environment

Jiang,

Chen,

Lin

et al. 2024

J. Phys.: Conf. Ser.

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The end-fire array is widely used in airborne radar systems for its specific physical configuration. However, mutual coupling is usually inevitable in the close-spaced end-fire array, which brings a great challenge for target detection in a clutter environment. In this paper, we investigate the effect of mutual coupling for the bistatic airborne radar with the end-fire array. Firstly, the signal model of the bistatic airborne radar with the end-fire array is presented. Then, the beam pattern and clutter model with mutual coupling are constructed. Furthermore, we analyze the clutter spectra with mutual coupling for different terrain types of the glistening zone. Finally, the simulation results validate the negative impact of the mutual coupling on target detection in clutter environment.

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Effects of Mutual Coupling for Bistatic Airborne Radar with End-fire Array in Clutter Environment

Jiang,

Chen,

Lin

et al. 2024

J. Phys.: Conf. Ser.

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A Novel Modified Symmetric Nested Array for Mixed Far-Field and Near-Field Source Localization

Xiang,

Jin,

Wang

et al. 2024

Remote Sensing

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In the process of locating mixed far-field and near-field sources, sparse nonlinear arrays (SNAs) can achieve larger array apertures and higher degrees of freedom compared to traditional uniform linear arrays (ULAs) with the same number of sensors. This paper introduces a Modified Symmetric Nested Array (MSNA), which can automatically generate the optimal array structure with the maximum continuous lags for a given number of sensors. To effectively address mixed source localization, we designed an estimation algorithm based on high-order cumulants and the subarray partition method, applied to the MSNA. Firstly, a specialized fourth-order cumulant matrix, relevant only to Direction of Arrival (DOA) information, is constructed for the DOA estimation of mixed sources. Then, peak searching using the estimated DOA information enables the estimation of the distance parameters, effectively separating mixed sources. The algorithm has moderate computational complexity and provides high resolution and estimation accuracy. Numerical simulation results demonstrate that, with the same number of physical sensors, the proposed MSNA provides more continuous lags than existing arrays, offering higher degrees of freedom and estimation accuracy.

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Sparse Polarimetric Array for MIMO System

Yue,

Liao,

Yuan

et al. 2024

Innovation in MIMO Systems [Working Title]

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To enhance sensing or communication capabilities, the utilization of extremely large multiple-input multiple-output transceiver arrays (EL-MIMO-TAs) with high array degrees-of-freedom (DoFs) holds significant promise for future applications, such as integrated sensing and communications systems. However, the implementation of EL-MIMO-TAs may face the problem of mutual coupling. It also necessitates a substantial number of radio frequency chains, leading to undesirable hardware costs. Consequently, there has been a growing interest in sparse array designs aimed at reducing mutual coupling and hardware expenses while maintaining a constant array DoFs. Nevertheless, conventional sparse arrays primarily benefit from spatial DoFs alone. A shift toward the development of sparse polarimetric arrays has emerged, offering low mutual coupling, and enhanced spatial DoFs along with the ability to exploit the polarimetric characteristics of electromagnetic waves. This chapter explores different strategies for designing sparse polarimetric arrays, focusing on the sparsity of array element positions—specifically, non-uniform, uniform, and hybrid non-uniform and uniform sparsity. Additionally, it introduces a novel method for estimating multi-dimensional parameters based on the reconstructed covariance matrix through data fitting, emphasizing low computational complexity. A new beamformer in the spatial-polarimetric joint domain is also presented, showcasing its ability to suppress main-lobe interferences and improved beamforming performance from a sparse reconstruction perspective.

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Generalized Widely Linear Robust Adaptive Beamforming: A Sparse Reconstruction Perspective

Cited by 3 publications

References 37 publications

Effects of Mutual Coupling for Bistatic Airborne Radar with End-fire Array in Clutter Environment

Effects of Mutual Coupling for Bistatic Airborne Radar with End-fire Array in Clutter Environment

A Novel Modified Symmetric Nested Array for Mixed Far-Field and Near-Field Source Localization

Sparse Polarimetric Array for MIMO System

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