浅海未爆弹磁异常探测和定位技术

Magnetic Anomaly Detection and Location Technology in Shallow Sea

摘要:

以海底未爆弹作为待测目标物,对其建立了偶极子磁异常探测模型,应用正交基检测算法(Orthogonal Basis Functions,OBFs)对获取的磁信号进行弱磁信号提取。结合GPS经纬度信息,提出处理海底磁异常数据的数据融合过程,然后创建地磁图来定位可疑的未爆弹(Unexploded Ordnance ,UXO)。通过仿真对算法处理流程进行分析。首先,利用有限元模拟方法对未爆弹在地磁背景下所产生的磁异常进行建模,然后模拟实际当中的空间采样过程,得到观测区采样信号图。通过插值的方法进行磁场的重构,最后获取异常源的位置信息。在未爆弹实际探测中,原始磁异常信号信噪比14.34dB。对原始磁异常数据进行滤波、正交基算法检测,信噪比20.04dB,显著提高了5.7dB。最终利用地磁图确定可能存在的未爆弹的经纬度位置。结果显示目标探测准确率达到100%,虚警率为零。该研究验证了磁异常探测在浅海掩埋未爆弹探测和定位的准确性和可靠性。

Abstract:

In this paper, the dipole magnetic anomaly detection model is developed to determine the underwater unexploded ordnances (UXOs). The weak magnetic signal is extracted from the acquired magnetic signal using the orthogonal basis (Orthogonal Basis Functions-OBFs) detection algorithm. In combination with GPS longitude and latitude information, the data fusion process is applied for processing seabed magnetic anomaly data, and then a geomagnetic map is created to locate the suspicious UXOs. The algorithmic processing flow is analyzed by simulation. Firstly, a finite element simulation method is used to model the magnetic anomaly generated by the buried objects under the geomagnetic background. And then the actual spatial sampling process is simulated to obtain the sampling signal map of the observation area. The magnetic field is reconstructed by interpolation method, and finally the location information of the anomaly source is obtained. In the practical application, the SNR of the original magnetic anomaly signal is 14.34dB. After filtering and OBFs signal processing, the SNR is enhanced to be 20.04dB, which is significantly increased by 5.7dB. Finally, we use the geomagnetic map to determine the longitude and latitude position of the unexploded bomb that may exist. The result shows that the accuracy of target detection reaches 100% and the false alarm rate is zero. This study verifies the accuracy and reliability of this proposed magnetic anomaly detection and location method for buried UXOs in shallow water.