Advanced signal processing algorithms based on novel nuclear quadrupole resonance models for the detection of explosives King's College London
- S D Somasundaram
- Advanced signal processing algorithms based on…
Nuclear quadrupole resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique, allowing the detection of compounds containing quadrupolar nuclei, a requirement fulfilled by many high explosives and narcotics. The practical use of NQR is restricted by the inherently low signal-to-noise ratio (SNR) of the observed signals, a problem that is further exacerbated by the presence of strong RF interference (RFI). The current literature focuses on the use of conventional, multiple-pulsed NQR (cNQR) to obtain signals. Here, we investigate an alternative method called stochastic NQR (sNQR), having many advantages over cNQR, one of which is the availability of signal-of-interest free samples. In this paper, we exploit these samples forming a matched subspace-type detector and a detector employing a prewhitening approach, both of which are able to efficiently reduce the influence of RFI. Further, many of the ideas already developed for cNQR, including providing robustness to uncertainties in the assumed complex amplitudes and exploiting the temperature dependencies of the NQR spectral components, are recast for sNQR. The presented detectors are evaluated on both simulated and measured trinitro-toluene (TNT) data.