Xie Taotao, Ji Qing, Yu Peng, Zhang Jiawei
Naval University of Engineering, Wuhan, China.
Naval Petty Officer Academy, Bengbu, China.
Sci Rep. 2025 Jul 29;15(1):27536. doi: 10.1038/s41598-025-12008-4.
To address the challenge of detecting small underwater targets, this paper proposes a detection method based on the fusion of acoustic and magnetic fields. The shaft-rate acoustic field and shaft-rate magnetic field of a vessel are both closely related to the rotation of its propeller and contain rich target characteristic information. Using the vessel's shaft-rate information as a key criterion, this paper proposes to fuse the acoustic and magnetic fields to extract the shaft-rate features of the vessel. Specifically, the line spectra of the shaft-rate acoustic and magnetic fields are first extracted using DEMON spectral analysis and power spectral analysis methods, respectively. Subsequently, the extracted line spectra are fused and purified. Finally, the shaft-rate features are extracted based on the greatest common divisor (GCD) method. To verify the effectiveness of the proposed method, real-measured acoustic and magnetic data from multiple vessels were used for experimental validation. The results show that there is a significant frequency correspondence between the line spectra of the shaft-rate acoustic and magnetic fields of the same vessel. By fusing the shaft-rate related line spectra of the acoustic and magnetic fields, the problem of line-spectrum loss in a single physical field, caused by environmental noise and other factors, can be effectively compensated. Moreover, after fusing the acoustic and magnetic fields, the accuracy and stability of the vessel's shaft-rate estimation are significantly better than those of a single physical field, allowing for more reliable extraction of shaft-rate information and enhancing the basis for target identification.
为应对小型水下目标探测的挑战，本文提出了一种基于声场与磁场融合的探测方法。船舶的轴频声场和轴频磁场均与螺旋桨的旋转密切相关，且包含丰富的目标特征信息。本文以船舶的轴频信息作为关键准则，提出融合声场与磁场以提取船舶的轴频特征。具体而言，首先分别采用解线谱分析（DEMON）和功率谱分析方法提取轴频声场和轴频磁场的线谱。随后，对提取的线谱进行融合与提纯。最后，基于最大公约数（GCD）方法提取轴频特征。为验证所提方法的有效性，利用多艘船舶的实测声学和磁学数据进行实验验证。结果表明，同一船舶的轴频声场和轴频磁场的线谱之间存在显著的频率对应关系。通过融合与轴频相关的声场和磁场线谱，可有效补偿由环境噪声等因素导致的单一物理场中线谱丢失的问题。此外，融合声场和磁场后，船舶轴频估计的准确性和稳定性显著优于单一物理场，能够更可靠地提取轴频信息，增强目标识别的依据。
