A hybrid full MAS and Combined MAS/TSA Algorithm for Electromagnetic Induction Sensing

نویسندگان

  • F. Shubitidze
  • K. O’Neill
  • K. Sun
  • I. Shamatava
  • K. D. Paulsen
چکیده

Electromagnetic induction (EMI) sensing, in both frequency and time domains, is emerging as one of the most promising remote sensing technologies for detection and discrimination of buried metallic objects, particularly unexploded ordinance (UXO). UXO sites are highly contaminated with metallic clutter so that the major problem is discrimination not detection. This requires high fidelity forward modeling for successful inversion and classification. Recently, the method of auxiliary sources (MAS) has been applied for solving a large range of ultra-wideband (1 Hz300 kHz) electromagnetic induction problems [1] [6]. For a highly conducting and permeable metallic object, when the skin depth becomes small (at high frequency, i.e. induction number >100) the efficiency of the MAS is reduced significantly [6]. Other methods are stressed in this region as well. At the same time the Thin Skin Approximation (TSA) [7] [9], which is based on the divergence free Maxwell's equation in a thin layer, infinitely close to the boundary interior, has shown very accurate results at high frequency/induction number. In this paper a hybrid algorithm, with standard MAS and also the MAS with TSA, is introduced and applied for solving the electromagnetic induction forward problem. Once the broadband frequency domain (FD) electromagnetic response is found it is translated into time domain (TD) using an inverse Fourier transform specialized for the characteristic TD input form. Numerical experiments are performed for highly conducting and permeable canonical objects, illuminated by a magnetic dipole or a loop antenna. These tests indicate that an algorithm using either the full MAS or MAS-TSA formulation, where appropriate, should provide a simulator that is applicable and efficient enough for fast 3-D solutions on a PC, under all conditions across the EMI band in both frequency and time domains.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fast direct and inverse EMI algorithms for enhanced identification of buried UXO with real EMI data - Geoscience and Remote Sensing Symposium, 2003. IGARSS '03. Proceedings. 2003 IEEE International

Discrimination of buried unexploded ordinance (UXO) from innocuous buried items remains a challenging, top priority problem for the electromagnetic induction (EMI) sensing community. In general, classification is an inverse problem, requiring very fast and accurate representation of the target response. To address this critical issue, this paper presents a very fast, rigorous way to compute EMI...

متن کامل

Perspective of MAS in Power System via a Fuzzy Framework

Multi agent systems (MAS) are popularly used in practice, however; a few studies have looked at MAS capabilities from the power engineering perspective. This paper presents the results of an investigation concerning the compatibility of MAS capabilities in different power engineering categories. Five MAS capabilities and seven power system categories are established. A framework for applying MA...

متن کامل

Comparing IDREAM as an Iterative Reconstruction Algorithm against In Filtered Back Projection in Computed Tomography

Introduction: Recent studies of Computed Tomography (CT) conducted on patient dose reduction have recommended using an iterative reconstruction algorithm and mA (mili-Ampere) dose modulation. The current study aimed to evaluate Iterative Dose Reduction Algorithm (IDREAM) as an iterative reconstruction algorithm. Material and Methods: Two CT p...

متن کامل

Multi-robot active sensing of non-stationary Gaussian process-based environmental phenomena Citation

A key challenge of environmental sensing and monitoring is that of sensing, modeling, and predicting large-scale, spatially correlated environmental phenomena, especially when they are unknown and non-stationary. This paper presents a decentralized multi-robot active sensing (DEC-MAS) algorithm that can efficiently coordinate the exploration of multiple robots to gather the most informative obs...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005