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Search Results (3)

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Keywords = VHVA

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21 pages, 16767 KiB  
Article
Research on the Supergain Properties and Influencing Factors of a Vector Hydrophone Vertical Array in the Deep Sea
by Yan Liang, Weixuan Zhang, Yu Chen and Zhou Meng
J. Mar. Sci. Eng. 2024, 12(8), 1273; https://doi.org/10.3390/jmse12081273 - 29 Jul 2024
Viewed by 1264
Abstract
Increasing array gains is one of the keys to improving underwater targets’ detection capabilities. This paper presents a high-gain approach for a vector hydrophone vertical array (VHVA) that combines white noise gain constraint (WNGC) with vector joint processing to preserve strong robustness and [...] Read more.
Increasing array gains is one of the keys to improving underwater targets’ detection capabilities. This paper presents a high-gain approach for a vector hydrophone vertical array (VHVA) that combines white noise gain constraint (WNGC) with vector joint processing to preserve strong robustness and provide noticeable gains. Firstly, this approach treats the VHVA as four independent sub-arrays and achieves sub-array supergains by decorrelating noise using WNGC. The beam outputs of the four sub-arrays are then equated to a single-vector hydrophone, the combination gain of which is obtained by leveraging the strong signal correlation and the weak noise correlation between the sound pressure and the particle velocity. Lastly, the sub-array supergain and combination gain are superposed to provide the spatial gain of the VHVA. It is also summarized that low-frequency signals, coherent noise, accurate elevation-angle estimation, and stable phase differences are required for the VHVA to achieve supergain. The simulation and sea trial confirm that this approach can effectively boost the array gain. The maximum spatial gain in the experiment was increased by 9 dB at a range twice the sea’s depth while operating at a low frequency. This method shows enormous potential for improving the performance of deep-sea target detection. Full article
(This article belongs to the Section Ocean Engineering)
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18 pages, 12364 KiB  
Article
A Deep-Sea Broadband Sound Source Depth Estimation Method Based on the Interference Structure of the Compensated Beam Output
by Yan Liang, Yu Chen, Zhou Meng, Xin Zhou and Yichi Zhang
J. Mar. Sci. Eng. 2023, 11(11), 2059; https://doi.org/10.3390/jmse11112059 - 28 Oct 2023
Cited by 4 | Viewed by 1543
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Section Physical Oceanography)
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21 pages, 6051 KiB  
Article
A Data Fusion Orientation Algorithm Based on the Weighted Histogram Statistics for Vector Hydrophone Vertical Array
by Yan Liang, Zhou Meng, Yu Chen, Yichi Zhang, Mingyang Wang and Xin Zhou
Sensors 2020, 20(19), 5619; https://doi.org/10.3390/s20195619 - 1 Oct 2020
Cited by 11 | Viewed by 2760
Abstract
In this paper, we propose a data fusion algorithm based on the weighted histogram statistics (DF-WHS) to improve the performance of direction-of-arrival (DOA) estimation for the vector hydrophone vertical array (VHVA). The processing frequency band is firstly divided into multiple sub-bands, and the [...] Read more.
In this paper, we propose a data fusion algorithm based on the weighted histogram statistics (DF-WHS) to improve the performance of direction-of-arrival (DOA) estimation for the vector hydrophone vertical array (VHVA). The processing frequency band is firstly divided into multiple sub-bands, and the high-resolution multiple signal classification (MUSIC) algorithm is applied to estimate the azimuth of each sub-band for each vector hydrophone. Then, the weighted least square (WLS) data fusion technique is used to fuse the sub-band estimation results of multiple sensors. Finally, the weighted histogram statistics method is employed to obtain the synthesis results in the frequency domain. We carried out a simulation and sea trial of the 16-element VHVA to evaluate the performance of the proposed algorithm. Compared to several traditional processing algorithms, the beam width of the proposed approach is significantly narrower, the side lobes are considerably lower, and the mean square error (MSE) is effectively smaller. In addition, the DF-WHS method is more suitable to accurately estimate the target azimuth with a low signal-to-noise ratio (SNR) because the noise sub-band is suppressed in the weighted histogram statistics step. The DF-WHS method in this article provides a new approach to improve the performance of deep-sea target detection for the VHVA. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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