Fast Localization and Characterization of Underground Targets with a Towed Transient Electromagnetic Array System

Abstract

A fast inversion algorithm combined with the transient electromagnetic (TEM) detection system has important significance for improving the detection efficiency of unexploded ordnance. The traditional algorithms, such as differential evolution or Gauss–Newton algorithms, usually require tens to thousands of iterations to locate the underground target. A new algorithm with a magnetic gradient tensor and singular value decomposition (SVD) to estimate the target position and characterization quickly and accurately is proposed in this paper. Two modes of magnetic gradient tensor are constructed to accurately locate shallow and deep targets, respectively. The SVD algorithm is applied to the responses to estimate the electromagnetic characteristics of the target quickly and accurately. To verify the performance of the proposed algorithm, a towed TEM sensor is designed, which is constructed with three transmitting coils and nine three-component receiving coils arranged in a 3 × 3 array. Field experiments in survey and cued modes were taken to verify the performance of the proposed algorithm and the towed system. Results show that the magnetic gradient tensor algorithm proposed in this paper can accurately locate a single target within 2.0 m depth, and the error of depth is no more than 8 cm. Even for overlapping response of multi targets, the error of depth is no more than 12 cm. The underground target can be accurately characterized by the SVD algorithm. For targets with depths over 2.0 m, the signal-to-noise ratio of characteristic response estimated by SVD is higher than that of the traditional method. The proposed method needs approximately 40 ms, only 1% of the traditional one, considerably improving detection efficiency and laying a theoretical and experimental foundation for real-time data processing.

On the Development of a Digital Twin for Underwater UXO Detection Using Magnetometer-Based Data in Application for the Training Set Generation for Machine Learning Models

“…For example, this topic was covered in [ 18 ], where the eigenvector decomposition of the magnetic gradient tensor was used to locate dipole-like magnetic sources, allowing automatic detection of dipole-like magnetic sources without estimating the magnetic moment direction. A similar approach has also been discussed in [ 19 ], where the authors proposed a new algorithm with a magnetic gradient tensor and singular value decomposition (SVD) to estimate the target position and characterization quickly and accurately.…”

Frequency Domain Electromagnetic System Based on Unmanned Aerial Vehicles Platform for Detecting Shallow Subsurface Targets

“…This part of the space is an area where human production and life are widely used [1]. The realization of the rapid and nondestructive detection of underground targets in this space has a wide range of application needs in urban construction [2,3], archaeological artifacts [4,5], unexploded ordnance (UXO) detection [6][7][8], and other fields. The main methods usually used to solve the problems of shallow subsurface targets detection are the magnetic detection method [9][10][11], ground penetrating radar (GPR) [12][13][14], and electromagnetic induction (EMI) method [15][16][17][18].…”

A Nine-Level Inverter with Adjustable Turn-Off Time for Helicopter Transient Electromagnetic Detection

“…The current pulse inverter should meet engineering indicators such as high power and fast turn-OFF time. The high power will provide the system with a more profound detection distance, and the faster turn-OFF time will provide the system with a better detection effect [ 14 , 15 , 16 , 17 , 18 , 19 ].…”