Optimization of scalar magnetic gradiometer signal processing

Lev Frumkis, Boris Ginzburg, Nizan Salomonski, Ben Zion Kaplan

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

The work is devoted to the detection of hidden ferromagnetic objects by employing a gradiometer comprising two scalar magnetic sensors. The hidden object is modeled by a magnetostatic dipole. Processing of the gradiometer signal is carried out by evaluation of the signal energy in the space of four orthonormal functions. This procedure is implemented within a moving window covering certain number of successive samples measured equidistantly along the survey track. This work proves that the width of the moving window (or the number of the samples within the window) can be optimized so to provide maximum signal-to-noise ratio. Removal of constant bias and linear temporal trend, usually accompanying the observed survey signal, has been proved as an important step in the data processing. The latter removal relies on linear regression procedure, and the related window width is also optimized. It is shown that the signal processing should depend on several survey channels operating simultaneously. Relying on the present work, a proper number of channels for multi-channel detection algorithm can be easily determined for each magnetic search scenario.

Original languageEnglish
Pages (from-to)88-94
Number of pages7
JournalSensors and Actuators, A: Physical
Volume121
Issue number1
DOIs
StatePublished - 31 May 2005

Keywords

  • Magnetic anomaly detection
  • Magnetic gradiometer
  • Orthonormal functions

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Metals and Alloys
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Optimization of scalar magnetic gradiometer signal processing'. Together they form a unique fingerprint.

Cite this