Synthetic adaptive matched field processing for moving source with a horizontal line array

2021 ◽  
Vol 149 (2) ◽  
pp. 1138-1146
Author(s):  
Fenghua Li ◽  
Feilong Zhu ◽  
Yanjun Zhang ◽  
Bo Zhang ◽  
Wen Li ◽  
...  
Keyword(s):  
Horizontal Line ◽  
Matched Field Processing ◽  
Moving Source ◽  
Line Array

scholarly journals Moving Source Depth Estimation Using a Horizontal Line Array in Shallow Water Waveguides

2018 ◽  
Author(s):  
Liang Guolong ◽  
Zhang Yifeng ◽  
Zou Nan ◽  
Wang Jinjin
Keyword(s):  
Shallow Water ◽  
Estimation Method ◽  
Depth Estimation ◽  
Propagation Model ◽  
Small Range ◽  
Horizontal Line ◽  
Source Depth ◽  
Moving Source ◽  
Line Array ◽  
Wavenumber Spectrum

In this study, a matched-mode autoregressive source depth estimation method (MMAR) based on autoregressive (AR) wavenumber estimation is proposed for a moving source in shallow water waveguides. The signal original frequency and the environmental parameters, namely, the sound speed profile and bottom properties are known as a prior knowledge. The mode wavenumbers are estimated by the AR modal wavenumber spectrum. On the basis of the mode wavenumber estimation, the mode amplitudes can be estimated by the wavenumber spectrum that is obtained by generalized Hankel transform. The source depth estimation is determined by the peak of source depth function wherein the data mode best matches the replica mode that is calculated using a propagation model. Compared with other methods of moving source depth estimation, the proposed method exhibits a better performance in source depth estimation under low signal-to-noise ratio or the small range span. The selection of horizontal line array depth is illustrated by simulation and normal mode theory in details.

Matched‐field processing of multi‐tone acoustic signals in shallow water with a horizontal line array

1997 ◽  
Vol 101 (5) ◽  
pp. 3048-3048
Author(s):  
Phil Schey ◽  
Newell O. Booth ◽  
Gary Dorrance ◽  
Al Aburto ◽  
William S. Hodgkiss
Keyword(s):  
Shallow Water ◽  
Acoustic Signals ◽  
Horizontal Line ◽  
Matched Field Processing ◽  
Line Array

scholarly journals Match-Mode Autoregressive Method for Moving Source Depth Estimation in Shallow Water Waveguides

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Liang Guo-Long ◽  
Zhang Yi-Feng ◽  
Zou Nan ◽  
Wang Jin-Jin
Keyword(s):  
Shallow Water ◽  
Depth Estimation ◽  
Propagation Model ◽  
Estimation Methods ◽  
Small Range ◽  
Horizontal Line ◽  
Source Depth ◽  
Moving Source ◽  
Line Array ◽  
Wavenumber Spectrum

Source depth estimation is always a problem in underwater acoustic area, because depth estimation is a nonlinear problem. Traditional depth estimation methods use a vertical line array, which has disadvantage of poor mobility due to the size of sensor array. In order to estimate source depth with a horizontal line array, we propose a matched-mode depth estimation method based on autoregressive (AR) wavenumber estimation for a moving source in shallow water waveguides. First, we estimate the mode wavenumbers using the improved AR modal wavenumber spectrum. Second, according to the mode wavenumber estimation, we estimate the mode amplitudes by the wavenumber spectrum, which is obtained by generalized Hankel transform. Finally, we estimate source depth estimation by the peak of source depth function wherein the data mode best matches the replica mode that is calculated using a propagation model. Compared with synthetic aperture beamforming, the proposed method exhibits a better performance in source depth estimation under low signal-to-noise ratio or the small range span. The robustness of the proposed method is illustrated by simulating the performance in mismatched environment.

scholarly journals Reliable Acoustic Path and Direct-Arrival Zone Spatial Gain Analysis for a Vertical Line Array

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3462 ◽  
Author(s):  
Chunyu Qiu ◽  
Shuqing Ma ◽  
Yu Chen ◽  
Zhou Meng ◽  
Jianfei Wang
Keyword(s):  
Sound Propagation ◽  
Correlation Coefficients ◽  
Deep Ocean ◽  
Vertical Line ◽  
Horizontal Line ◽  
Acoustic Path ◽  
Vertical Arrays ◽  
Peak Structure ◽  
Line Array ◽  
Propagation Properties

A method is developed in this paper to calculate the spatial gain of a vertical line array when the plane-wave assumption is not applicable and when the oceanic ambient noise is correlated. The proposed optimal array gain (OAG), which can evaluate the array’s performance and effectively guide its deployment, can be given by an equation in which the noise gain (NG) is subtracted from the signal gain (SG); hence, a high SG and a negative NG can enhance the performance of the array. OAGs and SGs with different array locations are simulated and analyzed based on the sound propagation properties of the direct-arrival zone (DAZ) and the reliable acoustic path (RAP) using ray theory. SG and NG are related to the correlation coefficients of the signals and noise, respectively, and the vertical correlation is determined by the structures of the multipath arrivals. The SG in the DAZ is always high because there is little difference between the multipath waves, while the SG in the RAP changes with the source-receiver range because of the variety of structure in the multiple arrivals. The SG under different conditions is simulated in this work. The “dual peak” structure can often be observed in the vertical directionality pattern of the noise because of the presence of bottom reflection and deep sound channel. When the directions of the signal and noise are close, the conventional beamformer will enhance the correlation of not only the signals but also the noise; thus, the directivity of the signals and noise are analyzed. Under the condition of having a typical sound speed profile, the OAG in some areas of the DAZ and RAP can achieve high values and even exceed the ideal gain of horizontal line array 10 logN dB, while, in some other areas, it will be lowered because of the influence of the NG. The proposed method of gain analysis can provide analysis methods for vertical arrays in the deep ocean under many conditions with references. The theory and simulation are tested by experimental data.

Sound speed profile inversion using a horizontal line array in shallow water

2014 ◽  
Vol 58 (1) ◽  
pp. 1-7 ◽  
Author(s):  
ZhengLin Li ◽  
Li He ◽  
RenHe Zhang ◽  
FengHua Li ◽  
YanXin Yu ◽  
...  
Keyword(s):  
Shallow Water ◽  
Sound Speed ◽  
Horizontal Line ◽  
Speed Profile ◽  
Sound Speed Profile ◽  
Line Array ◽  
Profile Inversion

scholarly journals Depth Discrimination for Low-Frequency Sources Using a Horizontal Line Array of Acoustic Vector Sensors Based on Mode Extraction

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3692 ◽  
Author(s):  
Guolong Liang ◽  
Yifeng Zhang ◽  
Guangpu Zhang ◽  
Jia Feng ◽  
Ce Zheng
Keyword(s):  
Sound Speed ◽  
Linear Equations ◽  
Robustness Analysis ◽  
Low Frequency ◽  
Horizontal Line ◽  
Testing Hypotheses ◽  
Depth Discrimination ◽  
Line Array ◽  
Vector Sensors ◽  
Mode Extraction

Depth discrimination is a key procedure in acoustic detection or target classification for low-frequency underwater sources. Conventional depth-discrimination methods use a vertical line array, which has disadvantage of poor mobility due to the size of the sensor array. In this paper, we propose a depth-discrimination method for low-frequency sources using a horizontal line array (HLA) of acoustic vector sensors based on mode extraction. First, we establish linear equations related to the modal amplitudes based on modal beamforming in the vector mode space. Second, we solve the linear equations by introducing the total least square algorithm and estimate modal amplitudes. Third, we select the power percentage of the low-order modes as the decision metric and construct testing hypotheses based on the modal amplitude estimation. Compared with a scalar sensor, a vector sensor improves the depth discrimination, because the mode weights are more appropriate for doing so. The presented linear equations and the solution algorithm allow the method to maintain good performance even using a relatively short HLA. The constructed testing hypotheses are highly robust against mismatched environments. Note that the method is not appropriate for the winter typical sound speed waveguide, because the characteristics of the modes differ from those in downward-refracting sound speed waveguide. Robustness analysis and simulation results validate the effectiveness of the proposed method.

scholarly journals Batch Processing through Particle Swarm Optimization for Target Motion Analysis with Bottom Bounce Underwater Acoustic Signals

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1234
Author(s):  
Raegeun Oh ◽  
Taek Lyul Song ◽  
Jee Woong Choi
Keyword(s):  
Particle Swarm Optimization ◽  
Motion Analysis ◽  
Acoustic Signals ◽  
Batch Processing ◽  
Target Motion ◽  
Horizontal Line ◽  
Swarm Optimization ◽  
Conical Angle ◽  
Line Array ◽  
Target Motion Analysis

A target angular information in 3-dimensional space consists of an elevation angle and azimuth angle. Acoustic signals propagating along multiple paths in underwater environments usually have different elevation angles. Target motion analysis (TMA) uses the underwater acoustic signals received by a passive horizontal line array to track an underwater target. The target angle measured by the horizontal line array is, in fact, a conical angle that indicates the direction of the signal arriving at the line array sonar system. Accordingly, bottom bounce paths produce inaccurate target locations if they are interpreted as azimuth angles in the horizontal plane, as is commonly assumed in existing TMA technologies. Therefore, it is necessary to consider the effect of the conical angle on bearings-only TMA (BO-TMA). In this paper, a target conical angle causing angular ambiguity will be simulated using a ray tracing method in an underwater environment. A BO-TMA method using particle swarm optimization (PSO) is proposed for batch processing to solve the angular ambiguity problem.

Sign in / Sign up

Export Citation Format

Share Document