Abstract
This chapter aims to be a literature review regarding the techniques applied for signal processing and analysis in nuclear quadrupole resonance detection applications. The chapter starts with a general classification, then it presents the pre- and post-processing techniques and, finally, the it discusses future research directions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Reprinted from J. of the Franklin Inst., vol. 357, issue 17, C. Monea, A review of NQR signal processing and analysis techniques, Pages 13,085–13,124, Copyright 2020, with permission from Elsevier [OR APPLICABLE SOCIETY COPYRIGHT OWNER].
References
Monea, C.: A review of NQR signal processing and analysis techniques. J. Franklin Inst. 357(17), 13085–13124 (2020)
Monea, C.: Signal processing and analysis methods in nuclear quadrupole resonance spectroscopy. J. Electrical Eng. Electron. Control Comput. Sci. 4(2), 1–8 (2018)
Butt, N.R., Gudmundson, E., Jakobsson, A.: An Overview of NQR Signal Detection Algorithms, Magnetic Resonance Detection of Explosives and Illicit Materials, pp. 19–33 (2013)
Hemnani, P., Joshi, G., Rajarajan, A.K., Ravindranath, S.V.: 14N NQR spectrometer for explosive detection: a review. Int. Conf. Automat. Control Dyn. Optimizat. Tech. (2016)
Xinwang, Z.: A Low-power Compact Nuclear Quadrupole Resonance (NQR) Based Explosive Detection System. Ph.D thesis, University of Nebraska, Lincoln (2014)
Tagare, P.: Signal Averaging, Biomedical Digital Signal Processing, pp. 184–192. Prentice-Hall (1993)
NMR Analysis.: Sensitivity Enhancement for free? Internet: http://nmr-analysis.blogspot.com/2008/07/sensitivity-enhancement-for-free.html. 13 Aug. 2020
Kyriakidou, G.: Medicine Authentication using Nuclear Quadrulope Resonance. Ph.D. thesis, King’s College London (2016)
Vaseghi, S.V.: Advanced Digital Signal Processing and Noise Reduction, Fourth edn. Wiley (2008)
Somasundaram, S.D., Althoefer, K., Smith, A.S., Seneviratne, L.D.: Detection of landmines using nuclear quadrupole resonance (NQR): Signal processing to aid classification. In: Climbing and Walking Robots, pp. 833–840 (2006)
Kronval, S., Kronval, T.: Detection of Illegal Narcotics Using NQR. Masters thesis, University of Lund (2012)
Gudmundson, E., Wirfalt, P., Jakobsson, A., Jansson, M.: An ESPRIT-based parameter estimator for spectroscopic data. IEEE Stat. Signal Process. Workshop (2012)
Jakobsson, A., Mossberg, M., Rowe, M.D., Smith, J.A.S.: Exploiting temperature dependency in the detection of NQR signals. IEEE Trans. Signal Process. 54(5), 1610–1616 (2006)
Jakobsson, A., Mossberg, M., Rowe, M.D., Smith, J.A.S.: Frequency-selective detection of nuclear quadrupole resonance signals. IEEE Trans. Geosci. Remote Sensing 43(11), 2659–2665 (2005)
Somasundaram, S.D., Jakobsson, A., Gudmundson, E.: Exploiting spin echo decay in the detection of nuclear quadrupole resonance signals. IEEE Trans. Geosci. Remote Sensing 45(4), 925–933 (2007)
Somasundaram, S.D., Jakobsson, A., Gudmundson, E.: Robust nuclear quadrupole resonance signal detection allowing for amplitude uncertainties. IEEE Trans. Signal Process. 56(3), 887–894 (2008)
Somasundaram, S.D., Jakobsson, A., Smith, J.A.S.: Analysis of nuclear quadrupole resonance signals from mixtures. Signal Process. 88(1), 146–157 (2008)
Butt, N., et al.: Robust detection of polymorphic NQR signals. In: 15th European Signal Processing Conference (EUSIPCO) (2007)
Somasundaram, S.D., et al.: Robust detection of stochastic nuclear quadrupole resonance signals. IEEE Trans. Signal Process. 56(9), 4221–4229 (2008)
Somasundaram, S.D., et al.: Detecting stochastic nuclear quadrupole resonance signals in the presence of strong radio frequency interference. In: IEEE International Conference on Acoustics, Speech and Signal Process (2008)
Somasundaram, S.D., Jakobsson, A., Butt, N.R.: Countering radio frequency interference in single-sensor quadrupole resonance. IEEE Geosci. Remote Sensing Lett. 6(1), 62–66 (2009)
Rudberg, T., Jakobsson, A.: Robust detection of nuclear quadrupole resonance signals in a non-shielded environment. In: Proceedings of the 19th European Signal Processing Conference (EUSIPCO) (2011)
Svensson, A., Jakobsson, A.: Adaptive detection of a partly known signal corrupted by strong interference. IEEE Signal Process. Lett. 18(12), 729–732 (2011)
Swärd, J., Jakobsson, A.: Canceling stationary interference signals exploiting secondary data. In: 22nd European Signal Processing Conference (EUSIPCO) (2014)
Shao, W., Barras, J., Althoefer, K., Kosmas, P.: Detecting NQR signals severely polluted by interference. Signal Proces 138, 256–264 (2017)
Shao, W., Kosmas, P., Althoefer, K., Barras, J.: Canceling strong and complex interference in NQR-based landmine detection. In: IEEE International Conference on Information and Automation for Sustainability (2016)
Shao, W., Barras, J., Kosmas, P.: A novel wavelets method for cancelling time-varying interference in NQR signal detection. Signal Process. 154, 238–249 (2019)
Hemnani, P., Rajarajan, A.K., Joshi, G., Ravindranath, S.V.G.: The building of pulsed NQR/NMR sSpectrometer. Int. J. Electri. Comput. Eng. 8(3), 1442–1450 (2018)
Hemnani, P., Rajarajan, A.K., Joshi, G., Ravindranath, S.V.G.: Detection of NQR signals using wavelet transform and adaptive filters. Int. J. Instrum. Tech. 2(1), 34–49 (2018)
Cardona, L.R.: Nuclear Quadrupole Resonance System for Landmine Detection in Antioquia. Ph.D. thesis, National University of Colombia (2017)
Shao, W., Barras, J., Kosmas, P.: Detection of extremely weak NQR signals using stochastic resonance and neural network theories. Signal Process. 142, 96–103 (2018)
Schiano, J., Routhier, T., Blauch, A.J., Ginsberg, M.D.: Feedback OPTIMIZATION OF PULSE WIdth in the SORC sequence. J. Magn. Reson. 140, 84–90 (1999)
Schiano, J., Blauch, A.J., Ginsberg, M.D.: Optimization of NQR pulse parameters using feedback control, Z. Naturforsch 55, 67–73 (2000)
Yang, T., et al.: NQR signal processing based on multi-stage wiener filter. Procedia Eng. 7, 229–234 (2010)
Apostolos, J.T., Feng, J., Mouyos, W., McMahon, B.: Using phase matched filters for NQR detection of continuous Rabi transitions. Patent, US8660803B2 (2011)
Mozzhukhin, G.V., Kupriyanova, G.S., Mershiev, I.G., Molchanov, S.V.: Signal processing in NMR/NQR detection on the base of pattern signal. In: 9th International Kharkiv Symposium on Physics and Engineering of Microwaves, Millimeter and Submillimeter Waves (2016)
Yingyi, T., Tantum, S.L., Collins, L.M.: Landmine detection with nuclear quadrupole resonance. IEEE International Symposium on Geoscience and Remote Sensing (2002)
Jiang, Y., Stoica, P., Li, J.: Array signal processing in the known waveform and steering vector case. IEEE Trans. Signal Process. 52(1), 23–35 (2004)
Tantum, S., et al.: Signal processing for NQR discrimination of buried landmines. In: SPIE Conference on Detection and Remediation Technologies for Mines and Minelike Targets IV, vol. 3710 (1999)
Stoica, P., Xiong, H., Xu, L., Li, J.: Adaptive beamforming for quadrupole resonance. Digital Signal Process. 17(3), 634–651 (2007)
Xiong, H.: Robust Adaptive Methods and Their Applications in Quadrupole Resonance. Ph.D. thesis, University of Florida (2006)
Liu, G., Jiang, Y., Xiong, H., Li, J., Barrall, G.A.: Radio frequency interference suppression for landmine detection by quadrupole resonance. EURASIP J. Appl. Signal Process. 2006, 1–14 (2006)
Xiong, H., Li, J., Barrall, G.A.: Joint TNT and RDX detection via quadrupole resonance. IEEE Trans. Aerospace Electron. Syst. 43(4), 1282–1293 (2007)
Shao, W., Barras, J., Kosmas, P.: An advanced beamforming approach based on two-channel echo-train system to cancel interference within an NQR signal resonance spectrum. Signal Process. 154, 136–147 (2019)
Jakobsson, A., Mossberg, M.: Using spatial diversity to detect narcotics and explosives using NQR signals. IEEE Trans. Signal Process. 55(9), 4721–4726 (2007)
Butt, N.R., Jakobsson, A., Somasundaram, S.D., Smith, J.A.S.: Robust multichannel detection of mixtures using nuclear quadrupole resonance. IEEE Trans. Signal Process. 56(10), 5042–5050 (2008)
Butt, N.R., Jakobsson, A.: Robust multi-sensor detection of polymorphic NQR signals. In: Conference on Record of the Forty-First Asilomar Conference on Signals, System and Computers (2007)
Butt, N.R., Jakobsson, A.: Efficient removal of noise and interference in multichannel quadrupole resonance. In: Conference on Record of the Forty Fifth Asilomar Conference on Signals, System and Computers (2011)
Piatti, T., Lei, S., Barras, J., Jakobsson, A.: Interference cancellation in two-channel nuclear quadrupole resonance measurements. IEEE Int. Conf. Acoustics Speech Signal Process. (2017)
Yingyi, T., Tantum, S.L., Collins, L.M.:, Kalman filtering for enhanced landmine detection using quadrupole resonance. IEEE Trans. Geosci. Remote Sensing 43(7), 1507–1516 (2005)
ScienceDirect.: Căutare articole despre machine learning. Internet: https://www.sciencedirect.com/search?qs=machine%20learning&show=25&sortBy=relevance. 13 Aug. 2020
Póczos, B., Singh, A.L.: Introduction to machine learning CMU-10701 Deep Learning. Carnegie Mellon University. Internet: http://www.cs.cmu.edu/~aarti/Class/10701_Spring14/slides/DeepLearning.pdf. 4 Jan. 2019
Lazebnik, L.: Convolutional neural network architectures: from LeNet to ResNet. University of Illinois. Internet: http://slazebni.cs.illinois.edu/spring17/lec01_cnn_architectures.pdf. 13 Aug. 2020
Stfalcon.: Deep learning: definition, benefits, and challenges. Internet: https://stfalcon.com/en/blog/post/deep-learning-benefits-and-challenges. 4 Jan. 2019
Liu, X., Li, R., Zhao, C., Wang, P.: Robust signal recognition algorithm based on machine learning in heterogeneous networks. J. Syst. Eng. Electron. 27(2), 333–342 (2016)
Klukowski, P., et al.: NMRNet: a deep learning approach to automated peak picking of protein NMR spectra. Bioinform. 34(15), 2590–2597 (2018)
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
4.1.1 Signal Processing and Analysis Techniques Classification
4.1.2 Signal Post-Processing and Analysis Techniques Development Timeline
4.1.3 Development of the Post-Processing Techniques
4.1.4 Distribution of the Post-Processing Techniques According to the Type of Detection [1]
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Monea, C., Bizon, N. (2022). Signal Processing and Analysis Techniques Applied in Nuclear Quadrupole Resonance. In: Signal Processing and Analysis Techniques for Nuclear Quadrupole Resonance Spectroscopy. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-87861-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-87861-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-87860-3
Online ISBN: 978-3-030-87861-0
eBook Packages: EngineeringEngineering (R0)