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| 3. |
- Butt, Naveed, et al.
(författare)
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An Overview of NQR Signal Detection Algorithms
- 2014
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Ingår i: Magnetic Resonance Detection of Explosives and Illicit Materials. - Dordrecht : Springer Netherlands. - 9789400772656 - 9789400772649 ; part 1, s. 19-33
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Bokkapitel (refereegranskat)abstract
- Nuclear quadrupole resonance (NQR) is a solid-state radio frequency spectroscopic technique that can be used to detect the presence of quadrupolar nuclei, that are prevalent in many narcotics, drugs, and explosive materials. Similar to other modern spectroscopic techniques, such as nuclear magnetic resonance, and Raman spectroscopy, NQR also relies heavily on statistical signal processing systems for decision making and information extraction. This chapter provides an overview of the current state-of-the-art algorithms for detection, estimation, and classification of NQR signals. More specifically, the problem of NQR-based detection of illicit materials is considered in detail. Several single- and multi-sensor algorithms are reviewed that possess many features of practical importance, including (a) robustness to uncertainties in the assumed spectral amplitudes, (b) exploitation of the polymorphous nature of relevant compounds to improve detection, (c) ability to quantify mixtures, and (d) efficient estimation and cancellation of background noise and radio frequency interference.
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| 4. |
- Butt, Naveed, et al.
(författare)
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Classification of Raman Spectra to Detect Hidden Explosives
- 2011
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X. ; 8:3, s. 517-521
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Tidskriftsartikel (refereegranskat)abstract
- Raman spectroscopy is a laser-based vibrational technique that can provide spectral signatures unique to a multitude of compounds. The technique is gaining widespread interest as a method for detecting hidden explosives due to its sensitivity and ease of use. In this letter, we present a computationally efficient classification scheme for accurate standoff identification of several common explosives using visible-range Raman spectroscopy. Using real measurements, we evaluate and modify a recent correlation-based approach to classify Raman spectra from various harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 m, or more, successfully classify measured Raman spectra from several explosive substances, including nitromethane, trinitrotoluene, dinitrotoluene, hydrogen peroxide, triacetone triperoxide, and ammonium nitrate.
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| 5. |
- Butt, Naveed, et al.
(författare)
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Coherence Spectrum Estimation From Nonuniformly Sampled Sequences
- 2010
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Ingår i: IEEE Signal Processing Letters. - 1070-9908. ; 17:4, s. 339-342
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Tidskriftsartikel (refereegranskat)abstract
- Magnitude squared coherence (MSC) is a useful bivariate spectral measure that finds application in a wide variety of fields. In this paper, we develop a nonparametric Capon-based MSC estimator that utilizes a segmented reformulation of the recently introduced iterative adaptive approach (IAA) to provide high resolution MSC spectrum estimates. The proposed estimator, termed segmented-IAA-MSC (or SIAA-MSC, for short), allows for unevenly sampled data as well as for sequences with arbitrarily missing samples. The estimator first uses segmented-IAA to find accurate estimates of the auto-and cross-covariance matrices of the given sequences. These estimates are then used in a Capon-based MSC estimator reformulated to allow for nonuniformly sampled sequences. To achieve higher statistical accuracy, the estimation problem is formulated so as to allow for overlapped segmentation of the available data. The proposed SIAA-MSC estimator is found to yield improved estimates as compared to the more commonly used least squares Fourier transform (LSFT) based MSC estimator.
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| 7. |
- Butt, Naveed, et al.
(författare)
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Efficient Removal of Noise and Interference in Multichannel Quadrupole Resonance
- 2011
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Konferensbidrag (refereegranskat)abstract
- We present an improved multichannel detection algorithm for use in nuclear quadrupole resonance (NQR) applications. The presented method exploits spatial diversity and additional noise-only data to efficiently remove spatially and temporally correlated noise and interference components from the measured data. Numerical investigations indicate that the “cleaner” data, thus obtained, allows for improved estimates of the NQR signal parameters. These improved estimates, in turn, lead to superior detection performance compared to the current state-of-the-art multichannel algorithms.
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| 8. |
- Butt, Naveed, et al.
(författare)
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Efficient Sparse Spectrum Estimation for Cognitive Radios
- 2012
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Ingår i: 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Proceedings of. - 9781467312394
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Konferensbidrag (refereegranskat)abstract
- The emerging concept of cognitive radios offers a way to use the limited radio-spectrum more efficiently by allowing networks and nodes to adaptively vary their parameters. An important element in the successful implementation of cognitive radios is the ability to estimate the varying state of spectrum usage in a wide-band channel quickly and at minimum cost. In this work, we utilize a powerful non-convex optimization approach to provide sparse and unbiased estimates of the spectrum from limited non-uniformly sampled data. Simulation results for a wide-band communication scenario show that the noise floor is significantly reduced compared to other commonly used approaches. This should help in reducing the miss-identification of occupied and vacant sub-bands of the spectrum, being a key requirement in spectrum sensing cognitive radios.
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| 9. |
- Butt, Naveed, et al.
(författare)
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High-Resolution Estimation of Multidimensional Spectra from Unevenly Sampled Data
- 2011
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Ingår i: Digital Signal Processing (DSP), 2011 17th International Conference on. - 9781457702730
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Konferensbidrag (refereegranskat)abstract
- Estimation of high-resolution multidimensional spectra from unevenly sampled limited sized data sets plays an important role in a large variety of signal processing applications. In this work, we develop a high-resolution non-parametric estimator for unevenly sampled N-dimensional data based on a recently introduced iterative method, the so-called iterative adaptive approach (IAA). The proposed estimator uses the definition of the multidimensional Fourier transform to obtain a frequency domain representation of the unevenly sampled signal. Using tensor algebra, the multidimensional frequency domain representation is then recast into matrix format and used in a weighted least squares (WLS) fitting criterion to iteratively obtain estimates of the spectral amplitudes and the covariance matrix. The proposed estimator is numerically shown to provide superior performance as compared to the commonly used least squares Fourier transform (LSFT) estimator.
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| 10. |
- Butt, Naveed R., et al.
(författare)
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An Improved Classification Scheme for Standoff Detection of Explosives via Raman Spectroscopy
- 2010
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Konferensbidrag (refereegranskat)abstract
- Raman spectroscopy is a laser-based vibrational tech- nique that can provide spectral signatures unique to a multitude of compounds. The technique is gaining widespread interest as a method for detecting hidden explosives due to its sensitivity and ease of use. In this work, we present a computationally e±cient clas- si¯cation scheme for accurate stando® identi¯cation of several common explosives using visible-range Raman spectroscopy. Using real measurements, we evaluate and modify a recent correlation-based approach to classify Raman spectra from various both harmful and commonplace substances. The results show that the proposed approach can, at a distance of 30 me- ters, or more, successfully classify measured Raman spectra from several explosive substances, including Nitromethane, TNT, DNT, Hydrogen Peroxide, TATP and Ammonium Nitrate.
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