Theoretical analysis of a new approach to order determination for a modified Prony method in swath mapping application

• Autorzy: Grall P. , Marszal J.
• Języki publikacji: EN

Abstrakty

EN

This article presents a new approach to determine the model order (number of principal components) in the modified Prony method applied to swath acoustic mapping. Determination of the number of principal components is a crucial step in the modified Prony method. In the proposed approach the model order is chosen based on the underlying physical model of the underwater acoustic environment, and utilised signal processing operations. This data-driven approach, attempts to make use of all available information to assess the number of signals arriving at the receiver using pipeline processing in lieu of iterative processing.

Słowa kluczowe

EN

swath bathymetry; interferometry; principal components; DOA; MBES

• Wydawca: Polskie Towarzystwo Akustyczne. Oddział Gdański
• Czasopismo: Hydroacoustics
• Rocznik: 2017
• Tom: Vol. 20
• Strony: 63--74
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Grall P.

• Gdańsk University of Technology Faculty of Electronics, Telecommunications and Informatics Department of Marine Electronic Systems Narutowicza 11/12,80-233 Gdańsk, Poland

autor

Marszal J.

• Gdańsk University of Technology Faculty of Electronics, Telecommunications and Informatics Department of Marine Electronic Systems Narutowicza 11/12,80-233 Gdańsk, Poland

Bibliografia

• [1] J. Akaeel , Fitting Models in Time Series Analysis, Journal Series Statistics, vol. 13, no. 1, pp 121-148, 1982.
• [2] B. Douglas, D. H. Johnson, Using the Sphericity Test for Source Detection with NarrowBand Passive Arrays, IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 38, no. 11, pp 2008-2015, 1990.
• [3] P. Grall, J. Marszal, Investigation into Interferometric Sonar System Accuracy, Hydroacoustics, vol.18, pp 69-76, 2015.
• [4] P. Grall, J. Marszal, Zastosowanie zmodyfikowanej metody Prony’ego do detekcji dna morskiego i obiektów podwodnych, Advances in Acoustics 2017, pp 563-574, 2017.
• [5] R.R. Hocking, R.L. Leslie, Selection of the Best Subset in Regression Analysis, Technometrix, vol. 9, no. 4, pp 531-540, 1967.
• [6] J. N. Holt, R. J. Antill, Determining the Number of Terms in a Prony Algorithm Exponential Fit, Mathematical Biosciences , vol. 36, pp 319-323, 1977.
• [7] G. Jin, D. Tang, Uncertainties of Differential Phase Estimation Associated with Interferometric Sonars, IEEE Journal of Oceanic Engineering, vol. 21, no. 1, pp 53-64, 1996.
• [8] P. H. Kraeutner, J. S. Bird, Principal Components Array Processing for Swath Acoustic Mapping, Proceedings of the IEEE Oceans’97 Conference, pp 1246-1255, 1997.
• [9] P. H. Kraeutner, J. S. Bird, Beyond Interferometry, Resolving Multiple Angles-of-Arrival in Swath Bathymetric Imaging, Proceedings of the IEEE Oceans’99 Conference, pp 37-46, 1999.
• [10] P. H. Kraeutner, J. S. Bird, B. Charbonneau, D. Bishop, F. Hegg, Multi-Angle Swath Bathymetry Sidescan Performance Analysis, Proceedings of the IEEE Oceans’02 Conference, pp 2253-2264, 2002.
• [11] R. Kumaresan, D.W. Tufts, L.L. Scharf, A Prony method for noisy data: Choosing the signal components and selecting the order in exponential signal models, Proceedings of the IEEE, vol. 72, no. 2, pp 230-233, 1984.
• [12] X. Lurton, Swath Bathymetry Using Phase Difference: Theoretical Analysis of Acoustical Measurement Precision, IEEE Journal of Oceanic Engineering, vol. 25, no. 3, pp 351-364, 2000.
• [13] Z. Li, H. Li, T. Zhou, Y. Yuan, Multiple sub-array beamspace CAATI algoritm for multibeam bathymetry system, Journal of Marine Science and Application, vol. 6, no. 1, pp 47-53, 2007.
• [14] B. D. Rao, K. S. Arun, Model Based Processing of Signals: A State Space Approach, Proceedings of the IEEE, vol. 80 no. 2, pp 283-310, 1992.
• [15] A. Rahman, K-B. Yu, Total Least Squares Approach for Frequency Estimation Using Linear Prediction, IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 35, no. 10, pp 1440-1455, 1987.
• [16] M. P. Ribeiro, D. J. Ewins, D. A. Robb, Non-Stationary Analysis and Noise Filtering Using a Technique Extended from the Original Prony Method, Mechanical Systems and Signal Processing, vol. 17, no. 3, pp 533-550, 2003.
• [17] D. W. Tufts, R. Kumaresan, Estimation of Frequencies of Multiple Sinusoids: Making Linear Prediction Perform Like Maximum Likelihood, Proceedings of the IEEE, vol. 70, no. 9, pp 975-990, 1982.
• [18] A-J. van der VEEN, E. F. Deprettere, A. L. Swindelehurst, Subspace-Based Signal Analysis Using Singular Value Decomposition, Proceedings of the IEEE, vol. 81, no. 9, pp 1277- 1309, 1993.
• [19] M. Wax, T. Kaliath, Detection of Signals by Information Theoretic Criteria, IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 33, no. 2, pp 387-393, 1985.
• [20] T. Zhou, H. Li, Z. Zhu, Y. Yuan, Application of modified multiple subarrays detection method to multibeam bathymetry system, Journal of Marine Science and Application, vol. 4, no. 2, pp 39-44, 2005.

Uwagi

PL

Opracowanie w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).