Sparse Bayesian learning for wideband direction-of-arrival estimation via beamformer power outputs in a strong interference environment

Zhang, Yahao; Yang, Yixin; Yang, Long; Wang, Yong

doi:10.1121/10.0009360

Cited by 3 publications

(6 citation statements)

References 18 publications

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“…By the end of 2021, as reported by Zhao et al [ 1 ], China's provinces and cities will increase public sport facilities, with a facility coverage rate of 23.4%, which can serve 478 million urban and rural residents [ 2 ], indicating that the allocation and management of public sport facilities resources is the key issue of public health. When the local government manages the resources of public sport facilities, it will produce a large amount of management information data and consume a lot of human, material, and financial resources.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities

Sun

2022

Journal of Environmental and Public Health

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With the improvement of people’s health awareness, the state increases the construction of public sport facilities, which complicates the allocation and management of resources. The existing spatial spectrum estimation method cannot eliminate the relevant interference data, resulting in duplicate data in the results of resource allocation and management, reducing the accuracy of resource allocation and management. In order to optimize the allocation and management of public sport facilities resources, this study proposes a spatial spectrum estimation method, which is used to deeply tap the potential information in public sport facilities resources and optimize the allocation and management. First, analyze the resources of public sport facilities and put forward the feature vector of allocation and management optimization. Then, use the spatial spectrum estimation method to learn the test samples, get the optimal threshold and weight, and build the resource allocation and management model of public sport facilities. Finally, the accuracy of spatial spectrum estimation method is 98% and the variation range is (0, 10), which is better than the accuracy of the original algorithm is 80% and the variation range is (0, 20). Moreover, change of the spatial spectrum estimation method is smoother, and the correlation between various analyses is better. In unit time, the amount of configuration and management data of spatial spectrum estimation method is higher than that of existing algorithms, which indirectly indicate that the configuration and management time of the spatial spectrum estimation method is short. At the same time, unstructured data account for a large proportion of the data tested this time. Therefore, the accuracy and variation range of the spatial spectrum estimation method is good, which is suitable for the construction of public sport facilities and realizes the optimization of resource allocation and management.

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Section: Introductionmentioning

confidence: 99%

[Retracted] A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities

Sun

2022

Journal of Environmental and Public Health

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“…Experimental data were collected by a tow array with 32 hydrophones uniformly spaced at 4 m, which was processed in [32]. Target1, target2 and target3 were, respectively, located at −18 • , −25 • , and −29 • .…”

Section: Resultsmentioning

confidence: 99%

“…The SBL-BPO method [32] uses VBI for Equation (12). In this method, given γ and σ l , the posterior distribution of p l is as follows:…”

Section: Proposed Methodsmentioning

confidence: 99%

“…Then, the initial noise parameter is given as follows. The posterior of the noise power is expressed as [32]…”

Section: Proposed Methodsmentioning

confidence: 99%

“…To achieve high estimation precision in a strong interference environment, we have proposed a method named BPO-based SBL (SBL-BPO) in [32]. Minimum variance distortionless response with diagonal loading (MVDR-DL) [33] is applied to suppress interference, since it adaptively produces a deep nulling to the direction of the interference and can suppress this interference sufficiently.…”

Section: Introductionmentioning

confidence: 99%

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Fast Sparse Bayesian Learning Based on Beamformer Power Outputs to Solve Wideband DOA Estimation in Underwater Strong Interference Environment

Zhang,

Liang,

Yang

et al. 2024

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Wideband direction-of-arrival (DOA) estimation is an important task for passive sonar signal processing. Nowadays, sparse Bayesian learning (SBL) attracts much attention due to its good performance. However, performance degrades in the existence of strong interference. This problem can be solved by combining the beamformer and the SBL. The beamformer is a useful tool to suppress interference. Then, the SBL can easily estimate the DOA of the targets from the beamformer power outputs (BPO). Unfortunately, the latter step needs to compute the matrix inversion frequently, which brings some computational burden to the sonar system. In this paper, the BPO-based SBL is modified. A sequential solution is provided for the parameters in the BPO probabilistic model. In this manner, only one signal precision parameter involved in the probabilistic model is updated in each iteration and the matrix inversion is avoided during the iteration, thus reducing the computational burden. Simulation and experimental results show that the proposed method maintains high estimation precision in the interference environment. At the same time, its computational efficiency is almost three times higher in comparison with state-of-the-art methods.

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Robust adaptive beamforming based on zone orthogonal constraint and steering vector estimation

Guo

Wang

Zhang

et al. 2023

JASA Express Letters

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This Letter solves steering vector estimation under mismatch for adaptive beamforming. The proposed beamformer implements a stepwise estimation of steering vector, and zone orthogonal constraint is added first based on adaptive constraint framework from Khabbazibasmenj [IEEE Trans. Signal Process. 60(6), 2974–2987 (2012)], which ensures that the estimated steering vector does not converge to an interference steering vector outside the predefined sector, even if the sector deviates from the central observation area of arrays. Then uncertainty set error constraint is used to improve the estimation accuracy. The numerical simulation and experimental results verify the effectiveness of the proposed method.

show abstract

Sparse Bayesian learning for wideband direction-of-arrival estimation via beamformer power outputs in a strong interference environment

Cited by 3 publications

References 18 publications

[Retracted] A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities

[Retracted] A Spatial Spectrum Estimation Method for Optimization and Improvement of Resource Allocation and Management of Public Sport and Health Facilities

Fast Sparse Bayesian Learning Based on Beamformer Power Outputs to Solve Wideband DOA Estimation in Underwater Strong Interference Environment

Robust adaptive beamforming based on zone orthogonal constraint and steering vector estimation

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