Wang Bo, Ren Guoquan, Li Zhining, Li Qingzhu, Cai Ziming
Department of Vehicle and Electrical Engineering, Shijiazhuang Branch, Army Engineering University of PLA, Shijiazhuang 050003, China.
Micromachines (Basel). 2022 Sep 29;13(10):1639. doi: 10.3390/mi13101639.
Currently, many small target localization methods based on a magnetic gradient tensor have problems, such as complex solution processes, poor stability, and multiple solutions. This paper proposes an optimization method based on the Euler deconvolution localization method to solve these problems. In a simulation, the Euler deconvolution method, an improved method of the Euler deconvolution method and our proposed method are analyzed under noise conditions. These three methods are evaluated in the field with complex magnetic interference in an experiment. The simulations show that the accuracy of the proposed method is higher than that of the improved Euler deconvolution method and is slightly lower for noisy conditions. The experimental results show that the proposed method is more precise and accurate than the Euler deconvolution and enhanced methods.
目前,许多基于磁梯度张量的小目标定位方法存在诸如求解过程复杂、稳定性差和多解等问题。本文提出一种基于欧拉反褶积定位方法的优化方法来解决这些问题。在一次模拟中,在噪声条件下对欧拉反褶积方法、欧拉反褶积方法的一种改进方法以及我们提出的方法进行了分析。在一次实验中,对这三种方法在具有复杂磁干扰的现场进行了评估。模拟结果表明,所提出方法的精度高于改进的欧拉反褶积方法,在有噪声条件下略低。实验结果表明,所提出的方法比欧拉反褶积方法和增强方法更精确、更准确。