Processing of radar data for landmine detection: nonlinear transformation

E. E. Bartosz; H. Duvoisin; R. Konduri; G. Z. Solomon

doi:10.1117/12.603704

10 June 2005 Processing of radar data for landmine detection: nonlinear transformation

E. E. Bartosz, H. Duvoisin, R. Konduri, G. Z. Solomon

Proceedings Volume 5794, Detection and Remediation Technologies for Mines and Minelike Targets X; (2005) https://doi.org/10.1117/12.603704
Event: Defense and Security, 2005, Orlando, Florida, United States

Abstract

The Handheld Standoff Mine Detection System (HSTAMIDS system) has achieved outstanding performance in government-run field tests due to its use of anomaly detection using principal component analysis (PCA) on the return of ground penetrating radar (GPR) coupled with metal detection. Indications of nonlinearities and asymmetries in Humanitarian Demining (HD) data point to modifications to the current PCA algorithm that might prove beneficial. Asymmetries in the distribution of PCA projections of field data have been quantified in Humanitarian Demining (HD) data. The data suggest a logarithmic correction to the data. Such a correction has been applied and has improved the FAR on this data set. The increase in performance is comparable to the increase shown using the simpler asymmetric rescaling method.

Citation Download Citation

E. E. Bartosz, H. Duvoisin, R. Konduri, and G. Z. Solomon "Processing of radar data for landmine detection: nonlinear transformation", Proc. SPIE 5794, Detection and Remediation Technologies for Mines and Minelike Targets X, (10 June 2005); https://doi.org/10.1117/12.603704

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