SVD for enhanced explosives detection using NQR

Abstract

Nuclear Quadrupole Resonance (NQR) is a solid-state radio frequency (RF) spectroscopic technique, allowing the detection of many high explosives and narcotics. Unlike metal detectors and ground penetrating radar (GPR), NQR detectors measure signals that are unique to the explosives, thus can provide a lower false alarm rate. 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), so a robust detection method is required. Singular value decomposition (SVD) based on Hankel matrix is proposed to detect the NQR signal in this paper. The original signal can be decomposed into the linear superposition of a series of component signals by SVD using Hankel matrix, and the process of constructing the Hankel matrix shows that a component T signal can be produced by averaging the elements on the inverse diagonal of the Ai=σiuiviT. Then an eigendecomposition based spectrum estimator called “Multiple Signal Characterization” (MUSIC) is applied to estimate power spectrum of each component signal, so the RFI and the noise are canceled by using the priori knowledge of the NQR frequency. Finally, an average power detector is applied to detect NQR signal. The result using measured data shows that the proposed method can provide robust NQR detection performance.