Multiple constraint matched field processing tolerant to array tilt mismatch

Byun, Gihoon; Akins, Franklin H.; Gemba, Kay L.; Song, H. C.; Kuperman, W. A.

doi:10.1121/10.0000784

Cited by 32 publications

(3 citation statements)

References 16 publications

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“…In summary, beamforming-based target direction estimation algorithms for underwater acoustic arrays can improve the performance of weak signal detection and underwater noise suppression, but the computational complexity of these algorithms needs to be considered. An additional important source of mismatch is the array tilt, which has not received much attention, in spite of its significant impact, especially for a large array tilt observed in shallow environments [14]. Other influential works in this field included Zhu et al and Zhang et al [15,16].…”

Section: Introductionmentioning

confidence: 99%

Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

Wang

et al. 2023

Remote Sensing

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Pulse noise (such as glacier fracturing and offshore pile driving), commonly seen in the marine environment, seriously affects the performance of Direction-of-Arrival (DOA) estimation methods in sonar systems. To address this issue, this paper proposes a high robustness underwater target estimation method based on variational sparse Bayesian inference by studying and analyzing the sparse prior assumption characteristics of signals. This method models pulse noise to build an observation signal, completes the derivation of the conditional distribution of the observed variables and the prior distribution of the sparse signals, and combines Variational Bayes (VB) theory to approximate the posterior distribution, thereby obtaining the recovered signal of the sparse signals and reducing the impact of pulse noise on the estimation system. Our simulation results showed that the proposed method achieved higher estimation accuracy than traditional methods in both single and multiple snapshot scenarios and has practical potential.

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Section: Introductionmentioning

confidence: 99%

Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

Wang

et al. 2023

Remote Sensing

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“…It requires all the characteristic data of the sound field environment; therefore, it is sensitive to environmental mismatches. Moreover, the uncertainty of the sound field environment significantly affects positioning performance (Bucker, 1976; Tran and Trinh, 2017; Worthmann et al , 2017; Byun et al , 2020). Finally, BF applied in the field of underwater passive localization usually assumes that the received signal is a spherical wave, which has high localization accuracy for near-field hydroacoustic targets (Somasundaram and Parsons, 2011; Somasundaram, 2012; Bi et al , 2017; Yuan et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

Underwater target passive acoustic localization method based on Hanbury Brown–Twiss interference

Liu

Zeng

Jian

et al. 2022

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Purpose Acoustic signals of the underwater targets are susceptible to noise, reverberation, submarine topography and biology, therefore it is difficult to precisely locate underwater targets. This paper proposes a new underwater Hanbury Brown-Twiss (HBT) interference passive localization method. This study aims to achieve precise location of the underwater acoustic targets. Design/methodology/approach The principle of HBT interference with ultrasensitive detection characteristics in optical measurements was introduced in the field of hydroacoustics. The coherence of the underwater target signal was analyzed using the HBT interference measurement principle, and the corresponding relationship between the signal coherence and target position was obtained. Consequently, an HBT interference localization model was established, and its validity was verified through simulations and experiments. Findings The effects of different array structures on the localization performance were obtained by simulation analysis, and the simulations confirmed that the HBT method exhibited a higher positioning accuracy than conventional beamforming. In addition, the experimental analysis demonstrated the excellent positioning performance of the HBT method, which verified the feasibility of the proposed method. Originality/value This study provides a new method for the passive localization of underwater targets, which may be widely used in the field of oceanic explorations.

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“…One of them is based on reducing the sensitivity of MFP through the use of a multiply constrained beamformer [8]. This suggests that opening up the search window in one or more of these parameters would make the beamformer more tolerant of uncertainty in the other parameters [6,9,10]. Another well-known approach is based on solving the problem of localization by incorporating environmental variability a priori [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Beamforming in multipath environment using the stable components of wave field

Virovlyansky¹

2020

Preprint

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The paper describes the beamforming procedures in an acoustic waveguide based on representing the field on the antenna as a superposition of several stable components formed by narrow beams of rays [A.L. Virovlyansky, J. Acoust. Soc. Am. 141, 1180-1189]. A modification of the matched field processing method is proposed, based on the transition from comparing the measured and calculated fields on the antenna to comparing their stable components. The modified approach becomes less sensitive to the inevitable inaccuracies of the environmental model. In the case of a pulsed source, the stable components carry signals whose arrival times can be taken as input parameters in solving the inverse problems. The use of the stable components as the initial fields on the aperture of the emitting antenna makes it possible to excite narrow continuous wave beams propagating along given ray paths.

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Multiple constraint matched field processing tolerant to array tilt mismatch

Cited by 32 publications

References 16 publications

Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

Underwater target passive acoustic localization method based on Hanbury Brown–Twiss interference

Beamforming in multipath environment using the stable components of wave field

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