Beampattern Synthesis via a Matrix Approach for Signal Power Estimation

Li, Jian; Xie, Yao; Stoica, Petre; Zheng, Xiayu; Ward, James E.

doi:10.1109/tsp.2007.899343

Cited by 39 publications

(3 citation statements)

References 41 publications

(83 reference statements)

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“…Several algorithms have been proposed to solve the signal power estimation problem. [10,11] DOA estimation is one of the important research areas of array signal processing and there exists at present a large number of algorithms for the problem. [12,13] For avoiding threshold α converging to zero, a penalty term −λ · lg α is incorporated into Equation 7.…”

Section: Proposed Methodsmentioning

confidence: 99%

A robust adaptive beamforming method based on iterative optimization algorithm

Zeng

Feng

2014

Journal of Electromagnetic Waves and Applications

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It is well known that the steering vector mismatch caused by estimating direction of arrival (DOA) error or array mutual coupling degrades severely the performance of adaptive beamforming. In this paper, we propose an adaptive robust beamforming algorithm to deal with this problem. The coupling coefficient between any two antenna elements can be calculated, and in the case of an uniform linear array, these coefficients can be represented by a symmetric Toeplitz matrix. The robust beamforming algorithm takes advantage of this specific structure of the symmetric Toeplitz matrix. Based on the criterion of maximum signal-to-interference-plus-noise ratio, the beamforming problem is transformed into an unconstrained optimization problem. A rough estimate of the DOA and power of desired signal are the only prior information of the proposed approach. The numerical simulations show that the proposed method can alleviate evidently the steering vector mismatch and ultimately improves the robustness of adaptive beamformers even encountering large DOA mismatch.

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Section: Proposed Methodsmentioning

confidence: 99%

A robust adaptive beamforming method based on iterative optimization algorithm

Zeng

Feng

2014

Journal of Electromagnetic Waves and Applications

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“…A two-stage algorithm for far-field wideband MIMO waveform design was suggested in [43] based on the Gerchberg-Saxton algorithm [44]. The key idea here is to obtain a complex-valued waveform in the spectral domain such that y u matches the magnitude of the desired beampattern as in (11).…”

Section: Problem Formulationmentioning

confidence: 99%

Near-Field Low-WISL Unimodular Waveform Design for Terahertz Automotive Radar

Eamaz¹,

Yeganegi²,

Mishra³

et al. 2023

Preprint

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Conventional sensing applications rely on electromagnetic far-field channel models with plane wave propagation. However, recent ultra-short-range automotive radar applications at upper millimeter-wave or low terahertz (THz) frequencies envisage operation in the near-field region, where the wavefront is spherical. Unlike far-field, the near-field beampattern is dependent on both range and angle, thus requiring a different approach to waveform design. For the first time in the literature, we adopt the beampattern matching approach to design unimodular waveforms for THz automotive radars with low weighted integrated sidelobe levels (WISL). We formulate this problem as a unimodular bi-quadratic matrix program, and solve its constituent quadratic sub-problems using our cyclic power method-like iterations (CyPMLI) algorithm. Numerical experiments demonstrate that the CyPMLI approach yields the required beampattern with low autocorrelation levels.

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“…6 Weighting algorithms may be used to obtain a fixed mainlobe across the frequency spectrum. 7,8 Methods based on the design of specialized array geometries for sidelobe elimination have also been proposed. 9,10 Adaptive beamforming methods may achieve improved resolution with reduced sidelobes provided that the number of snapshots is sufficiently large.…”

Section: Introductionmentioning

confidence: 99%

Wideband compressive beamforming tomography for drive-by large-scale acoustic source mapping

Tuna

Jones

Zhao

et al. 2018

The Journal of the Acoustical Society of America

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Noise-mapping is an effective sound visualization tool for the identification of urban noise hotspots, which is crucial to taking targeted measures to tackle environmental noise pollution. This paper develops a high-resolution wideband acoustic source mapping methodology using a portable microphone array, where the joint localization and power spectrum estimation of individual sources sparsely distributed over a large region are achieved by tomographic imaging with the multi-frequency delay-and-sum beamforming power outputs from multiple array positions. Exploiting the fact that a wideband source has a common spatial signal-support across the frequency spectrum, two-dimensional tomographic maps are produced by applying compressive sensing techniques including group least absolute shrinkage selection operator formulation and sparse Bayesian learning to promote group sparsity over multiple frequency bands. The high-resolution mapping is demonstrated with experimental data recorded with a microphone array mounted atop an electric vehicle driven along a road while playing audio clips from a loudspeaker positioned within the adjacent open field.

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Beampattern Synthesis via a Matrix Approach for Signal Power Estimation

Cited by 39 publications

References 41 publications

A robust adaptive beamforming method based on iterative optimization algorithm

A robust adaptive beamforming method based on iterative optimization algorithm

Near-Field Low-WISL Unimodular Waveform Design for Terahertz Automotive Radar

Wideband compressive beamforming tomography for drive-by large-scale acoustic source mapping

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