Adaptive multimodality sensing of landmines
The problem of adaptive multimodality sensing of landmines is considered based on electromagnetic induction (EMI) and ground-penetrating radar (GPR) sensors. Two formulations are considered based on a partially observable Markov decision process (POMDP) framework. In the first formulation, it is assumed that sufficient training data are available, and a POMDP model is designed based on physics-based features, with model selection performed via a variational Bayes analysis of several possible models. In the second approach, the training data are assumed absent or insufficient, and a lifelong-learning approach is considered, in which exploration and exploitation are integrated. We provide a detailed description of both formulations, with example results presented using measured EMI and GPR data, for buried mines and clutter. © 2007 IEEE.
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Related Subject Headings
- Geological & Geomatics Engineering
- 40 Engineering
- 37 Earth sciences
- 0909 Geomatic Engineering
- 0906 Electrical and Electronic Engineering
- 0404 Geophysics
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Geological & Geomatics Engineering
- 40 Engineering
- 37 Earth sciences
- 0909 Geomatic Engineering
- 0906 Electrical and Electronic Engineering
- 0404 Geophysics