A Small Target Localization Method Based on the Magnetic Gradient Tensor

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.

Automated summary

This paper proposes an optimization method based on the Euler deconvolution localization method to address the issues faced by small target localization methods based on a magnetic gradient tensor. Simulation results show that the proposed method has higher accuracy compared to the improved Euler deconvolution method. Experimental results further validate that the proposed method is more precise and accurate compared to the Euler deconvolution and enhanced methods.