Sensor Data Fusion for Spectroscopy-Based Detection of Explosives
In-situ trace detection of explosive compounds such as RDX, TNT, and ammonium nitrate, is an important problem for the detection of IEDs and IED precursors. Spectroscopic techniques such as LIBS and Raman have shown promise for the detection of residues of explosive compounds on surfaces from standoff distances. Individually, both LIBS and Raman techniques suffer from various limitations, e.g., their robustness and reliability suffers due to variations in peak strengths and locations. However, the orthogonal nature of the spectral and compositional information provided by these techniques makes them suitable candidates for the use of sensor fusion to improve the overall detection performance. In this paper, we utilize peak energies in a region by fitting Lorentzian or Gaussian peaks around the location of interest. The ratios of peak energies are used for discrimination, in order to normalize the effect of changes in overall signal strength. Two data fusion techniques are discussed in this paper. Multi-spot fusion is performed on a set of independent samples from the same region based on the maximum likelihood formulation. Furthermore, the results from LIBS and Raman sensors are fused using linear discriminators. Improved detection performance with significantly reduced false alarm rates is reported using fusion techniques on data collected for sponsor demonstration at Fort Leonard Wood.
P. V. Shah et al., "Sensor Data Fusion for Spectroscopy-Based Detection of Explosives," Proceedings of Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV (2009, Orlando, FL), vol. 7303, SPIE, Apr 2009.
The definitive version is available at https://doi.org/10.1117/12.819902
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIV (2009: Apr. 13-17, Orlando, FL)
Electrical and Computer Engineering
Keywords and Phrases
RDX; TNT; Detection; Explosive Compounds; Residue; Ammonium Nitrate; Compostional Information; Data Fusion Technique; Detection Of Explosives; Detection Performance; Explosive Compounds; False Alarm Rate; Fusion Techniques; Gaussian Peaks; IED Detection; In-Situ; LIBS; Linear Discriminator; Peak Energy; Peak Strength; Raman Sensors; Raman Techniques; Region-Based; Sensor Fusion; Signal Strengths; Spectroscopic Technique; Standoff Distance; TEPS; Trace Detection; Ammonium Compounds; Explosives; Information Fusion; Location; Maximum Likelihood; Mining; Nitration; Raman Scattering; Raman Spectroscopy; Sensors; Trace Analysis; Sensor Data Fusion; Data Fusion
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Article - Conference proceedings
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