Abstract
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.
Subject
Electrical and Electronic Engineering,Mechanical Engineering,Control and Systems Engineering
Reference17 articles.
1. Li, Q., Li, Z., Zhang, Y., and Yin, G. (2018). Artificial vector calibration method for differencing magnetic gradient tensor systems. Sensors, 18.
2. Selecting a discrimination algorithm for unexploded ordnance remediation;IEEE Trans Geosci. Remote Sens.,2008
3. Using the ratio of the magnetic field to the analytic signal of the magnetic gradient tensor in determining the position of simple shaped magnetic anomalies;J. Geophys. Eng.,2017
4. 6-D magnetic localization and orientation method for an annular magnet based on a closed-form analytical model;IEEE Trans. Magn.,2014
5. Quantitative Analysis of the Measurable Areas of Differential Magnetic Gradient Tensor Systems for Unexploded Ordnance Detection;IEEE Sens. J.,2020