A Modified Differential Beamforming and Its Application for DOA Estimation of Low Frequency Underwater Signal

Xu, Zhezhen; Li, Hui; Yang, Kunde

doi:10.1109/jsen.2020.2988025

Cited by 18 publications

(4 citation statements)

References 33 publications

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“…For beamforming, various algorithms have been presented in literature, e.g., conventional classic beamforming [30,31,32], minimum norm beamforming (MINNORM), Multiple Signal Classification Algorithm (MUSIC), root-MUSIC, Estimation of signal parameters via rotation invariance techniques (ES-PRIT), minimum variance distortionless response algorithm (MVDR), etc. [33,34,35].…”

Section: Tft-csdm Doa Estimatormentioning

confidence: 99%

Cross power spectral density based beamforming for underwater acoustic communications

Bai

Zhang

et al. 2020

Ocean Engineering

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Section: Tft-csdm Doa Estimatormentioning

confidence: 99%

Cross power spectral density based beamforming for underwater acoustic communications

Bai

Zhang

et al. 2020

Ocean Engineering

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“…Deconvolution is also widely used to improve resolution. Both [ 36 , 37 ] explored how to improve resolution. Ref.…”

Section: Introductionmentioning

confidence: 99%

“…Ref. [ 36 ] considers the case that acoustic signals receive signals at a lower frequency than the designed way. They proposed a differential beamforming method and combined it with deconvolution to reduce the width of the beam power.…”

Section: Introductionmentioning

confidence: 99%

An Optimal Subspace Deconvolution Algorithm for Robust and High-Resolution Beamforming

Miao

Sun

et al. 2022

Sensors

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Utilizing the difference in phase and power spectrum between signals and noise, the estimation of direction of arrival (DOA) can be transferred to a spatial sample classification problem. The power ratio, namely signal-to-noise ratio (SNR), is highly required in most high-resolution beamforming methods so that high resolution and robustness are incompatible in a noisy background. Therefore, this paper proposes a Subspaces Deconvolution Vector (SDV) beamforming method to improve the robustness of a high-resolution DOA estimation. In a noisy environment, to handle the difficulty in separating signals from noise, we intend to initial beamforming value presets by incoherent eigenvalue in the frequency domain. The high resolution in the frequency domain guarantees the stability of the beamforming. By combining the robustness of conventional beamforming, the proposed method makes use of the subspace deconvolution vector to build a high-resolution beamforming process. The SDV method is aimed to obtain unitary frequency matrixes more stably and improve the accuracy of signal subspaces. The results of simulations and experiments show that when the input SNR is less than −27 dB, signals of decomposition differ unremarkably in the subspace while the SDV method can still obtain clear angles. In a marine background, this method works well in separating the noise and recruiting the characteristics of the signal into the DOA for subsequent processing.

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“…Direction-of-Arrival (DOA) estimation technologies are widely used in the modern radar and communication systems [1][2][3][4][5] . In the past decades, researchers have presented many super-resolution estimation methods.…”

Section: Introductionmentioning

confidence: 99%

Multi-DOA Estimation Based on the KR Image Tensor and Improved CNN

Yuan

Yang

et al. 2021

Preprint

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In this paper, we propose an improved convolutional neural network (CNN) to solve the multi-DOA estimation problem. We use Khatri-Rao (KR) product to obtain the KR image tensor of covariance matrix and use the proposed estimation CNN to process the tensor. In order to increase the generalization of the proposed CNN and adapt the multi-label classification problem, we use the curriculum learning scheme (CLS) and partial label strategy (PLS) to develop an efficient training procedure. We implement several experiments to demonstrate the satisfying performance of the proposed estimation method. The simulation results show that our proposed method can finish the high resolution multi-DOA estimation use only a few sensors. Furthermore, the proposed method can obtain high estimation accuracy under low SNR situations and use fewer snapshots.

show abstract

A Modified Differential Beamforming and Its Application for DOA Estimation of Low Frequency Underwater Signal

Cited by 18 publications

References 33 publications

Cross power spectral density based beamforming for underwater acoustic communications

Cross power spectral density based beamforming for underwater acoustic communications

An Optimal Subspace Deconvolution Algorithm for Robust and High-Resolution Beamforming

Multi-DOA Estimation Based on the KR Image Tensor and Improved CNN

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