Preprocessing of 8- to 12-μm polarimetric features for laid and flush-buried mine detection

Larive, M.; Spoliansky, D.; Trezieres, O.

doi:10.1117/12.357008

Cited by 5 publications

(1 citation statement)

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“…After or during a conflict, one may deploy airborne sensors to determine where possible mine fields reside, with these interrogated subsequently via ground‐based sensors. While airborne mine detection (via radar [ Carin et al , 1999] or infrared [ Larive et al , 1999] sensors) is very challenging, the fact that one is often only interested in sensing a mine field, rather than each individual mine, implies that one need not detect every target to detect the mine field (i.e., the detection probability for individual mines may be low, and one may still detect high‐density mine fields).…”

Section: Introductionmentioning

confidence: 99%

Analysis of wideband forward looking synthetic aperture radar for sensing land mines

Kovvali

Carin

2004

Radio Science

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[1] Signal processing algorithms are considered for the analysis of wideband, forward looking synthetic aperture radar data and for sensing metal and plastic land mines, with principal application to unpaved roads. Simple prescreening algorithms are considered for reduction of the search space required for a subsequent classifier. The classifier employs features based on viewing the target at multiple ranges, with classification implemented via a support vector machine and a relevance vector machine (RVM). Concerning classifier training, we consider cases for which training is performed on both mine and nonmine (clutter) data. In addition, motivated by the fact that the clutter statistics may vary significantly between the training and testing data, we also consider RVM implementation when we only train on mine data.

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Section: Introductionmentioning

confidence: 99%