Passive Source Localization Using Acoustic Intensity in Multipath-Dominant Shallow-Water Waveguide

Kim, Sunhyo; Cho, Sung-Ho; Jung, Seom‐Kyu; Choi, Jee Woong

doi:10.3390/s21062198

Cited by 3 publications

(3 citation statements)

References 31 publications

(89 reference statements)

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“…In order to obtain the simplification of phase shifts, an intermediate function is built to denote the squared root term in (3), which is given by…”

Section: System Modelmentioning

confidence: 99%

“…The complexity of the RD-MUSIC algorithm mainly depends on two major processes: angle estimations and range estimation, denoted as 2n e [((3M − 1)M 2 + (M + 1))/2 + 3(M + 1) 3 /8] + (2M) 2 J + (2M) 3 and n l (2M)[(2M) 2 + 1], respectively, where n e = π/∆ represents the number of spectral peak searches in the angle domain, n l represents the number of spectral peak searches in the distance interval, and is the search step.…”

Section: Complexity Analysismentioning

confidence: 99%

“…The source localization is one of the key techniques for target detection in radars [1,2]. In underwater sonar systems, the location of submerged sources is usually regarded as parameter estimation in the near field due to the relatively large array aperture [3,4]. In the field of Internet of Vehicles, the direction of arrival (DOA) estimation of landmark signal also belongs to one type of the near-field source localization [5,6].…”

Section: Introductionmentioning

confidence: 99%

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Three-Dimensional Source Localization with Sparse Symmetric Cross Array

Shi

2022

Sensors

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Three-dimensional (3-D) localization information, including elevation angle, azimuth angle, and range, is important for locating a single source with spherical wave-fronts. Aiming to reduce the high computational complexity of the classical 3-D multiple signal classification (3D-MUSIC) localization method, a novel low-complexity reduced-dimension MUSIC (RD-MUSIC) algorithm based on the sparse symmetric cross array (SSCA) is proposed in this article. The RD-MUSIC converts the 3-D exhaustive search into three one-dimensional (1-D) searches, where two of them are obtained by a two-stage reduced-dimension method to find the angles, and the remaining one is utilized to obtain the range. In addition, a detailed complexity analysis is provided. Simulation results demonstrate that the performance of the proposed algorithm is extremely close to that of the existing rank-reduced MUSIC (RARE-MUSIC) and 3D-MUSIC algorithms, whereas the complexity of the proposed method is significantly lower than that of the others, which is a big advantage in practice.

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“…In order to obtain the simplification of phase shifts, an intermediate function is built to denote the squared root term in (3), which is given by…”

Section: System Modelmentioning

confidence: 99%

Section: Complexity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Three-Dimensional Source Localization with Sparse Symmetric Cross Array

Shi

2022

Sensors

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The Formation of 2D Holograms of a Noise Source and Bearing Estimation by a Vector Scalar Receiver in the High-Frequency Band

Pereselkov,

Kuz’kin,

Ehrhardt

et al. 2024

JMSE

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The holographic signal-processing method for a single vector scalar receiver (VSR) in the high-frequency band in shallow water is developed in the paper. The aim of this paper is to present the results of the theoretical analysis, numerical modeling, and experimental verification of holographic signal processing for a noise source by the VSR. The developed method is based on the formation of the 2D interferogram and 2D hologram of a noise source in a shallow-water waveguide. The 2D interferograms and 2D holograms for different channels of the VSR (P sound pressure and VX and VY vibration velocity components) are considered. It is shown that the 2D interferogram consists of parallel interference fingers in the presence of a moving noise source. As a result, the 2D hologram contains focal points located on a straight line, and the angular distribution of the holograms has the main extreme value. It is shown in the paper that the holographic signal-processing method allows detecting the source, estimating the source bearing, and filtering the useful signal from the noise. The results of the source detection, source bearing estimation, and noise filtering are presented within the framework of experimental data processing and numerical modeling.

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Estimation of Source Range and Location Using Ship-Radiated Noise Measured by Two Vertical Line Arrays with a Feed-Forward Neural Network

Jo,

Choi,

Han

2024

JMSE

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Machine learning-based source range estimation is a promising method for enhancing the performance of tracking both the dynamic and static positions of targets in the underwater acoustic environment using extensive training data. This study constructed a machine learning model for source range estimation using ship-radiated noise recorded by two vertical line arrays (VLAs) during the Shallow-water Acoustic Variability Experiment (SAVEX-15), employing the Sample Covariance Matrix (SCM) and the Generalized Cross Correlation (GCC) as input features. A feed-forward neural network (FNN) was used to train the model on the acoustic characteristics of the source at various distances, and the range estimation results indicated that the SCM outperformed the GCC with lower error rates. Additionally, array tilt correction using the array invariant-based method improved range estimation accuracy. The impact of the training data composition corresponding to the bottom depth variation between the source and receivers on range estimation performance was also discussed. Furthermore, the estimated ranges from the two VLA locations were applied to localization using trilateration. Our results confirm that the SCM is the more appropriate feature for the FNN-based source range estimation model compared with the GCC and imply that ocean environment variability should be considered in developing a general-purpose machine learning model for underwater acoustics.

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Passive Source Localization Using Acoustic Intensity in Multipath-Dominant Shallow-Water Waveguide

Cited by 3 publications

References 31 publications

Three-Dimensional Source Localization with Sparse Symmetric Cross Array

Three-Dimensional Source Localization with Sparse Symmetric Cross Array

The Formation of 2D Holograms of a Noise Source and Bearing Estimation by a Vector Scalar Receiver in the High-Frequency Band

Estimation of Source Range and Location Using Ship-Radiated Noise Measured by Two Vertical Line Arrays with a Feed-Forward Neural Network

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