Landmine detection and localization using chemical sensor array processing

We develop methods for automatic detection and localization of landmines using chemical sensor arrays and statistical signal processing techniques. The transport of explosive vapors emanating from buried landmines is modeled as a diffusion process in a two-layered system consisting of ground and air...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 48; no. 5; pp. 1295 - 1305
Main Authors: Jeremic, A., Nehorai, A.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.05.2000
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Applied sciences
Array signal processing
Chemical sensors
Detectors
Diffusion processes
Exact sciences and technology
Explosives
Information, signal and communications theory
Landmine detection
Maximum likelihood estimation
Sensor arrays
Sensors
Signal and communications theory
Signal processing algorithms
Signal, noise
Studies
Telecommunications and information theory
Testing
Performance evaluation
Waveform
Parameter estimation
Fourier transformation
Physical model
Diffusion process
Mathematical model
Target detection
Cramer Rao inequality
Object location
Probabilistic approach
Measurement sensor
Chemical sensor
False alarm rate
Statistical method
Stratified medium
Experimental result
Algorithm performance
Automatic measurement
Statistical model
Likelihood ratio test
Signal processing
Numerical simulation
Explosives
Maximum likelihood
Measurement method
Explosive emission
Sensor array
Concentration distribution
ISSN:1053-587X, 1941-0476
Online Access:Get full text
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Description
Summary:We develop methods for automatic detection and localization of landmines using chemical sensor arrays and statistical signal processing techniques. The transport of explosive vapors emanating from buried landmines is modeled as a diffusion process in a two-layered system consisting of ground and air. Measurement and statistical models are then obtained from the associated concentration distribution. We derive two detectors (the generalized likelihood ratio (GLR) test and the mean detector) and determine their performance in terms of the probabilities of false alarm and detection. To determine the unknown location of a landmine, we derive a maximum likelihood (ML) estimation algorithm and evaluate its performance by computing the Cramer-Rao bound (CRB). The results are applied to the design of chemical sensor arrays, satisfying criteria specified in terms of detection and estimation performance measures and for optimally selecting the number and positions of sensors and the number of time samples. To illustrate the potential of the proposed techniques in a realistic demining scenario, we derive a moving-sensor algorithm in which the stationary sensor array is replaced by a single moving sensor. Numerical examples are given to demonstrate the applicability of our results.
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ISSN:1053-587X
1941-0476
DOI:10.1109/78.839977