磁强计
标量(数学)
计算机科学
水下
物理
粒子群优化
磁场
算法
控制理论(社会学)
数学
人工智能
几何学
量子力学
海洋学
地质学
控制(管理)
作者
Zhen Wang,Shengwei Liu,Yanguo Guo,Yongpeng Wu,Yi Wang,Jing Zhao
标识
DOI:10.1109/lgrs.2023.3315319
摘要
Autonomous Underwater Vehicle (AUV) with towed Magnetic Anomaly Detection (MAD) system is a reliable technique for detecting underwater magnetic targets. However, arranging too many magnetometers in the towed MAD system is not suitable, and the key lies in their reasonable arrangement. As a result, this paper proposes a new MAD system equipped with two scalar and one vector magnetometers, along with the corresponding multi-parameter magnetic target localization method. By using two scalar magnetometers and the geometric relationship with vector magnetometer, the time when the vector magnetometer reaches the closest point approach (CPA) on the trajectory and the value range of the shortest distance are obtained. The value range of the shortest distance is cleverly set as the search boundary for the improved particle swarm optimization algorithm in this dimension, which greatly mitigates the randomness of the optimization algorithm and enhances the accuracy of the solution. Subsequently, the unique solution for the magnetic target parameters can be easily obtained by using the vector magnetometer. The combination of scalar and vector magnetometers proves to be both economical and effective. Numerical simulation and field experiments show that this method provides a new idea for static magnetic target detection.
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