基于磁异常信号解析的目标速度特性研究

Research on Target Speed Characteristics Based on Magnetic Anomaly Signal Analysis

摘要:

水下磁性目标产生的磁场成为重要的水下目标非声探测信号源，因此对水下磁性目标的静磁场建模原理开展了研究。实现了均匀磁化的旋转椭球体模型和磁偶极子模型，并对 2 种模型在目标磁异常信号仿真上的适应性进行了分析。研究表明：相比于磁偶极子模型，旋转椭球体模型在传感器与目标距离较近时也能表现很好的适应性。由此，利用旋转椭球体模型，首先通过仿真计算构建了目标在不同运动速度状态下的近距离磁异常信号数据集，然后开展基于深度学习方法的水下磁性目标运动速度识别方法研究，最后识别效果在验证集和测试集上分别取得了 0.17 m/s 和 0.74 m/s 良好的误差精度，为后续目标的航向等状态识别奠定重要基础。

Abstract:

Magnetic fields generated by underwater magnetic targets become an important source of non-acoustic detection signals for underwater targets. In this paper，the principles of static magnetic field modeling of underwater magnetic targets are investigated. The rotating ellipsoid model with uniform magnetization and the magnetic dipole model are implemented，and the adaptability of the two models to the simulation of target magnetic anomaly signal is analyzed. The results show that the rotating ellipsoid model can also perform well when the sensor is close to the target compared to the magnetic dipole model. Therefore，using the rotating ellipsoid model，we firstly construct the close-range magnetic anomaly signal dataset of the target in different motion speed states by simulation，and then carry out the research on the underwater magnetic target motion speed recognition method based on the deep learning method. Finally，the recognition effect achieves good error accuracy，which is 0.17 m/s on the validation set and 0.74 m/s on the test set，and the work of this paper lays an important foundation for the subsequent target heading and other state recognition.