Intelligent Order-Based Method for Synthesis of NRF Spectra and Detection of Hazardous Materials

Clandestine transport of hazardous materials has been recognized as a major challenge for global aviation, water and land transport and homeland security. Nuclear resonance fluorescence (NRF) provides a high-potential physics basis for efficient detection of such materials at the entry points of a country. NRF's potency, however, is diminished due to varying environmental conditions and noisy background. Hence, fast and accurate signal processing algorithms are needed for detection and diagnostic purposes. In this paper a new method for identification of hazardous materials is proposed. The synergy of NRF signal processing and fuzzy logic allows an automated procedure for the detection of such materials. Automated decision making that does not require human interference improves the speed of the algorithm execution. The proposed method is tested on various scenarios aiming at the detection of Uranium-238 in NRF spectra.