A theoretical performance analysis and simulation of time-domain EMI sensor data for land mine detection

被引:16
|
作者
Gao, P [1 ]
Collins, LM [1 ]
机构
[1] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27708 USA
来源
关键词
D O I
10.1109/36.851785
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
In this paper, the physical phenomenology of electromagnetic induction (EMI) sensors is reviewed for application to land mine detection and remediation, The response from time-domain EMI sensors is modeled as an exponential damping as a function of time, characterized by the initial magnitude and decay rate. Currently deployed EMI sensors that are used for the land mine detection process the recorded signal in a variety of ways in order to provide an audio output for the operator to judge whether or not the signal is from a mine. Sensors may sample the decay curve, sum it, or calculate its energy. Based on exponential decay model and the assumption that the sensor response is subject to additive white Gaussian noise, the performance of these, as well as optimal, detectors are derived and compared. Theoretical performance predictions derived using simplifying assumptions are shown to agree closely with simulated performance. It will also be shown that the generalized likelihood ratio test (GLRT) is equivalent to the likelihood ratio test (LRT) for multichannel time-domain EMI sensor data under the additive while Gaussian noise assumption and specific assumptions regarding the Statistics of the decay rates of targets and clutter.
引用
收藏
页码:2042 / 2055
页数:14
相关论文
共 50 条
  • [1] Wideband frequency- and time-domain EMI for mine detection
    Carin, L
    Won, IJ
    Keiswetter, D
    DETECTION AND REMEDIATION TECHNOLOGIES FOR MINES AND MINELIKE TARGETS IV, PTS 1 AND 2, 1999, 3710 : 14 - 25
  • [2] A theoretical limit and simulation of time-domain event detection in the EEG
    Watkins, Paul V.
    Doolittle, Luke M.
    Krusienski, Dean J.
    Anderson, Nicholas R.
    2015 7TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2015, : 1020 - 1023
  • [3] On the Statistical Properties of the Peak Detection for Time-Domain EMI Measurements
    Azpurua, Marco A.
    Pous, Marc
    Silva, Ferran
    IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, 2015, 57 (06) : 1374 - 1381
  • [4] Multifrequency analysis with time-domain simulation
    Usaola, J
    Mayordomo, JG
    EUROPEAN TRANSACTIONS ON ELECTRICAL POWER, 1996, 6 (01): : 53 - 60
  • [5] Spectrum Analysis and EMI Measurements aced on Time-Domain Methods
    Braun, Stephan
    PROCEEDINGS OF THE 15TH CONFERENCE ON MICROWAVE TECHNIQUES, COMITE 2010, 2010, : 13 - 17
  • [6] Spectral representation, a core aspect of modelling the response characteristics of time-domain EMI mine detectors
    West, G. F.
    Bailey, R. C.
    DETECTION AND REMEDIATION TECHNOLOGIES FOR MINES AND MINELIKE TARGETS XI, PTS 1 AND 2, 2006, 6217
  • [7] Time-domain analysis of sensor-to-sensor transmissibility operators
    Aljanaideh, Khaled F.
    Bernstein, Dennis S.
    AUTOMATICA, 2015, 53 : 312 - 319
  • [8] TIME-DOMAIN SIMULATION ANALYSIS OF AVALANCHE PHOTODETECTORS
    RIAD, SM
    RIAD, AAR
    IEEE TRANSACTIONS ON ELECTRON DEVICES, 1982, 29 (06) : 994 - 998
  • [9] Fast Time-Domain Simulation for Reliable Fault Detection
    Tasic, Bratislav
    Dohmen, Jos J.
    Janssen, Rick
    ter Maten, E. Jan W.
    Pulch, Roland
    Beelen, Theo G. J.
    PROCEEDINGS OF THE 2016 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE), 2016, : 301 - 306
  • [10] Measurement-Based Equivalent Circuit Model for Time-Domain Simulation of EMI Filters
    Negri, Simone
    Spadacini, Giordano
    Grassi, Flavia
    Pignari, Sergio
    2022 INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY (EMC EUROPE 2022), 2022, : 793 - 798