Volume 12, no. 2Pages 97 - 111

Recursive Multi-Channel Matrix Pencil Method

O.L. Ibryaeva, A.L. Shestakov, I.I. Fedosov
The Matrix Pencil Method (MPM) approximates the input signal by a sum of complex exponentials. The method works well in many applications (high resolution DOA estimation, time-domain signal prediction, Coriolis Mass Flow Meter (CMF) signal processing). There are many modifications of the classical MPM, among which we mention the Recursive MPM capable of tracking signal parameters in the sliding window mode, and Multi-Channel MPM capable of processing several signals simultaneously which have the same poles. For example, this situation takes place in CMF signal processing where two sensors signals have the same frequencies for all vibration modes. The paper is devoted to combining these two techniques in the Recursive Multi-Channel MPM. This modification allows to track effectively the parameters of several signals with the same poles in the sliding window mode. Algorithms of all methods are summarized; a simulation example is given.
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Keywords
matrix pencil method; recursive estimation; singular value decomposition (SVD); updating and downdating SVD; Coriolis Mass Flow Meter signal processing.
References
1. Hua Y., Sarkar T.K. Matrix Pencil Method for Estimating Parameters of Exponentially Damped/Undamped Sinusoids in Noise. IEEE Transactions on Acoustics, Speech and Signal Processing, 1990, vol. 38, no. 5, pp. 814-824. DOI: 10.1109/29.56027
2. Crow M.L., Singh A. The Matrix Pencil for Power System Modal Extraction. IEEE Transactions on Power Systems, 2005, vol. 20, no. 1, pp. 501-502. DOI: 10.1109/TPWRS.2004.841158
3. Drissi K.E.K., Poljak D. The Matrix Pencil Method Applied to Smart Monitoring and Radar. Computational Methods and Experimental Measurements XVII, 2016, vol. 59, pp. 13-24. DOI: 10.2495/CMEM150021
4. Persichkin A., Shpilevoy A. About the Method of Estimating the Parameters of Seismic Signals. IKBU's Vestnik. Series: Physics, Mathematics, And Technology, 2015, no. 10, pp. 122-125. (in Russian)
5. Hossein Q., Hojjat A. A Comparative Study of Signal Processing Methods for Structural Health Mnitoring. Journal of Vibroengineering, 2016, vol. 18, no. 4, pp. 2186-2204. DOI: 10.21595/jve.2016.17218
6. Ibryaeva O., Salov D. Matrix Pencil Method for Coriolis Mass Flow Meter Signal Processing in Two-Phase Flow Conditions. International Conference on Industrial Engineering, Applications and Manufacturing, 2017, pp. 1-4. DOI: 10.1109/ICIEAM.2017.8076363
7. Tombs M., Zhou F., Henry M. Two-Phase Coriolis Mass Flow Metering with High Viscosity Oil. Flow Measurement and Instrumentation, November, 2017, vol. 59, pp. 23-27. DOI: 10.1016/j.flowmeasinst.2017.11.009.
8. Henry M., Tombs M., Duta M., Zhou F. Two-Phase Flow Metering of Heavy Oil Using a Coriolis Mass Flow Meter: A Case Study. Flow Measurement and Instrumentation, 2006, vol. 17, no. 6, pp. 399-413. DOI: 10.1016/j.flowmeasinst.2006.07.008
9. Yaqing Tu, Huiyue Yang, Haitao Zhang, Xiangyu Liu. CMF Signal Processing Method Based on Feedback Corrected ANF and Hilbert Transformation. Measurement Science Review, 2014, vol. 14, no. 1, pp. 41-47. DOI: 10.2478/msr-2014-0007
10. Li Ming, Henry M. Complex Bandpass Filtering for Coriolis Mass Flow Meter Signal Processing. Industrial Electronics Society, 2016, pp. 4952-4957. DOI: 10.1109/IECON.2016.7793040
11. Ibryaeva O., Semenov A., Henry M. Measurement Validation for ICPS: Matrix Pencil Method for Coriolis Metering with Liquid/Gas Flow. IEEE Industrial Cyber-Physical Systems, 2018, p. 6. DOI: 10.1109/ICPHYS.2018.8390745
12. Ibryaeva O., Taranenko P. Matrix Pencil Method for Coriolis Metering with Liquid/Gas Flow II: Experimental Results. IEEE Industrial Cyber-Physical Systems, 2018, p. 6. DOI: 10.1109/ICPHYS.2018.8390744
13. Enrique J., Rio F., Sarkar T.K. Comparison Between the Matrix Pencil Method and the Fourier Transform Technique for High-Resolution Spectral Estimation. Digital Signal Processing, 1996, vol. 6, pp. 108-125. DOI: 10.1006/dspr.1996.0011
14. Biao Lu, Dong Wei, Evans B.L., Bovik A.C. Improved Matrix Pencil Methods. Conference Record of Thirty-Second Asilomar Conference on Signals, Systems and Computers, 1997, pp. 1433-1437.
15. Steffens A., Rebentrost P., Marvian I. An Efficient Quantum Algorithm for Spectral Estimation. New Journal of Physics, 2017, vol. 19, pp. 1-14. DOI: 10.1088/1367-2630/aa5e48
16. Ibryaeva O. Recursive Matrix Pencil Method. 2nd International Ural Conference on Measurements, 2017, p. 6. DOI: 10.1109/URALCON.2017.8120739
17. Brand M. Fast Low-Rank Modifications of the Thin Singular Value Decomposition. Linear Algebra and Its Applications, 2006, vol. 415, no. 1, pp. 20-30. DOI: 10.1016/j.laa.2005.07.021
18. Henry M.P., Ibryaeva O.L., Salov D.D., Semenov A.S. Matrix Pencil Method for Estimation of Parameters of Vector Processes. Bulletin of the South Ural State University. Series: Mathematical Modelling, Programming and Computer Software, 2017, vol. 10, no. 4, pp. 92-104. DOI: 10.14529/mmp170409
19. Yilmazer N., Ari S., Sarkar T.K. Multiple Snapshot Direct Data Domain Approach and ESPRIT Method for Direction of Arrival Estimation. Digital Signal Processing, 2018, pp. 561-567. DOI: 10.1016/j.dsp.2007.07.004
20. Henry M., Leach F., Davy M., Bushuev O. The Prism: Efficient Signal Processing for the Internet of Things. IEEE Industrial Electronics Magazine, 2017, pp. 22-32. DOI: 10.1109/MIE.2017.2760108
21. Henry M. An Introduction to Prism Signal Processing Applied to Sensor Validation. Measurement Techniques, 2018, pp. 1233-1237. DOI: 10.1007/s11018-018-1345-1