Passive broadband source depth estimation in the deep ocean using a single vector sensor

Qi, Yubo; Zhou, Shihong; Liang, Yuquan; Du, Shuyuan; Liu, Changpeng

doi:10.1121/10.0001627

Cited by 17 publications

(3 citation statements)

References 9 publications

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“…Therefore, they have become increasingly popular in deep-sea environments in recent years. Qi et al [22] and Li et al [23] employed a single vector hydrophone positioned near the seafloor to obtain the arrival angle and then estimated source depth based on the interference period of the received sound intensity spectrum. According to the estimated depth, Li further performed range estimation.…”

Section: Introductionmentioning

confidence: 99%

A Deep-Sea Broadband Sound Source Depth Estimation Method Based on the Interference Structure of the Compensated Beam Output

Liang,

Chen,

Meng

et al. 2023

JMSE

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This paper proposes an underwater broadband target depth estimation method based on the multipath arrival structure in medium and short-range deep-sea environments. The proposed approach involves separating the multipath rays arriving at the vertical line array using the matched filtering technique. The combined beamforming is then applied to the vector hydrophone vertical array (VHVA) to obtain more accurate elevation angle estimates. The components of the interference sound field at different distances are judged, and the signal received by the array is compensated using suitable estimated angles. Finally, the multipath time delay difference is extracted from the pulse peaks of the compensated signal, and the target depth is estimated by establishing the relationship among the multipath time delay difference, the elevation angle and depth. Simulations and experiments demonstrate the effectiveness of this method in reducing the depth estimation bias and avoiding the misjudgment of surface or submerged targets.

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Section: Introductionmentioning

confidence: 99%

A Deep-Sea Broadband Sound Source Depth Estimation Method Based on the Interference Structure of the Compensated Beam Output

Liang,

Chen,

Meng

et al. 2023

JMSE

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“…Cao et al [16] applied a convolutional neural network to vector data and proposed a method of DOA estimation using an SVS based on deep transfer learning. Qi et al [17] used the interference cycle in the frequency domain to extract the source depth from signals recorded by an ocean-bottom seismometer (OBS) at a low frequency from 20 to 100 Hz.…”

Section: Introductionmentioning

confidence: 99%

“…Qi et al. [17] used the interference cycle in the frequency domain to extract the source depth from signals recorded by an ocean‐bottom seismometer (OBS) at a low frequency from 20 to 100 Hz.…”

Section: Introductionmentioning

confidence: 99%

A multi‐step method for passive broadband source localisation using a single vector sensor

Wang

Lin

et al. 2022

IET Radar Sonar & Navi

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In the deep ocean, a vector sensor is deployed near the seabed to receive direct waves from the reliable acoustic path (RAP). In the space domain, the vector sensor can estimate the vertical arrival azimuth of the signal, which is sensitive to distance. In the frequency domain, the periodic interference pattern formed by the direct and surfacereflected wave is decided by both the source depth and the vertical arrival azimuth. In this work, a multi-step method for passive broadband source localisation using a single-vector sensor (SVS) is proposed. At first, the depth is estimated by the interference pattern in the frequency domain. Then the ranging problem is solved based on the depth estimated result. The impact of the surface-generated noise is considered. Compared with the scalar vertical line array (VLA) in simulation, the localisation performance of SVS has higher requirements for the signal-to-noise ratio (SNR) but is much smaller in size. In the experiment, Gaussian white noise from 310 to 430 Hz was emitted to simulate the underwater target. Compared with traditional match-field processing (MFP), the multi-step method is much more stable, accurate, and efficient. The computing time is drastically shortened.

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Direction finding based on iterative adaptive approach utilizing weighted $$\ell _2$$-norm penalty for acoustic vector sensor array

Wang

Tan

Shi

et al. 2021

Multidim Syst Sign Process

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Passive broadband source depth estimation in the deep ocean using a single vector sensor

Cited by 17 publications

References 9 publications

A Deep-Sea Broadband Sound Source Depth Estimation Method Based on the Interference Structure of the Compensated Beam Output

A Deep-Sea Broadband Sound Source Depth Estimation Method Based on the Interference Structure of the Compensated Beam Output

A multi‐step method for passive broadband source localisation using a single vector sensor

Direction finding based on iterative adaptive approach utilizing weighted $$\ell _2$$-norm penalty for acoustic vector sensor array

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