Inversion Optimization for Underground Dynamic Target Detection

Underground metal target detection technology is widely used in various fields. One of the electromagnetic induction methods obtains the secondary field data in a region firstly and then uses the model inversion to estimate the parameters of metal targets. However, the traditional method must keep the detector horizontal in the detection process, and if not, the inversion results are inaccurate. Therefore, it is necessary to study the inversion algorithms for the dynamic detection environment. In this paper, a dynamic forward model was established for the dynamic detection environment at first. We utilized the attitude information of the detector to transform the observation coordinate system and then calculated the secondary field. Secondly, the objective function with these data was constructed for the optimization methods. Finally, two inversion algorithms, the conjugate gradient method and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm, were used in this study to compare the obtained results. According to the simulation results and the performance of the algorithms so as to validate the feasibility of the proposed dynamic model and results meet the detection requirements.