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Liya Xu, Yi Ma, Jinfeng Zhang, Bin Liao. Wideband Direction-of-Arrival Estimation Based on Deep Learning[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2021, 30(4): 412-424. doi: 10.15918/j.jbit1004-0579.2021.079
Citation: Liya Xu, Yi Ma, Jinfeng Zhang, Bin Liao. Wideband Direction-of-Arrival Estimation Based on Deep Learning[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2021, 30(4): 412-424.doi:10.15918/j.jbit1004-0579.2021.079
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Wideband Direction-of-Arrival Estimation Based on Deep Learning

doi:10.15918/j.jbit1004-0579.2021.079

  • Shenzhen University, Shenzhen 518060, China

Funds:This work was supported in part by the National Natural Science Foundation of China (No. 62101340).
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  • Author Bio:

    Liya Xu(xuliya@szu.edu.cn) received the B.Eng. degree in communication engineering from Information Engineering University, Zhengzhou, China, in 2011, and received the Ph.D. degree in Underwater Acoustic Engineering with Northwestern Polytechnical University, Xi’an, China, in 2019. From April 2019 to December 2021, she is a postdoctoral researcher in the College of Information Engineering, Shenzhen University, Shenzhen, China. Her research interests include passive source localization, geoacoustic inversion, and sound propagation

    Yi Ma(617462529@qq.com) received the B.Eng. degree from Guangdong University of Petrochemical Technology in 2017 and M. Eng degree from Shenzhen University in 2021. His main research interests are array signal processing, deep learning and its applications

    Jinfeng Zhang(zhangjf@szu.edu.cn) received the Ph.D. degree in signal and information processing from Dalian University of Technology, Dalian, China, in 2017. She is currently an associate professor in the faculty of College of Electronics and Information Engineering, Shenzhen University, and she also serves as a member of the Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University. Her research interests include array signal processing and Non-Gaussian signal processing and their applications

    Bin Liao(binliao@szu.edu.cn) received the B.Eng. and M.Eng degrees from Xidian University, Xi’an, China, in 2006 and 2009, respectively, and received his Ph.D. degree from The University of Hong Kong, Hong Kong, in 2013. From September 2013 to January 2014, he was a Research Assistant with the Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong. From August 2016 to October 2016, he was a Research Scientist with the Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong. He is currently an Associate Professor in the College of Information Engineering, Shenzhen University, Shenzhen, China. He is a recipient of the Best Paper Award at the 21st International Conference on Digital Signal Processing (2016 DSP) and 22nd International Conference on Digital Signal Processing (2017 DSP). His research interests include sensor array processing, adaptive filtering, convex optimization, with applications to radar, navigation and communications. Dr. Liao is currently a member of the Sensor Array and Multichannel (SAM) Technical Committee of the IEEE Signal Processing Society. He was an Associate Editor of IEEE ACCESS from 2017 to 2019. He is currently an Associate Editor of IEEE Transactions on Aerospace and Electronic Systems, IET Signal Processing, and Multidimensional Systems and Signal Processing

  • Corresponding author:zhangjf@szu.edu.cn
  • Received Date:2021-10-28
  • Rev Recd Date:2021-11-19
  • Accepted Date:2021-11-26
  • Publish Date:2021-12-27
    Abstract
  • The performance of traditional high-resolution direction-of-arrival (DOA) estimation methods is sensitive to the inaccurate knowledge on prior information, including the position of array elements, array gain and phase, and the mutual coupling between the array elements. Learning-based methods are data-driven and are expected to perform better than their model-based counterparts, since they are insensitive to the array imperfections. This paper presents a learning-based method for DOA estimation of multiple wideband far-field sources. The processing procedure mainly includes two steps. First, a beamspace preprocessing structure which has the property of frequency invariant is applied to the array outputs to perform focusing over a wide bandwidth. In the second step, a hierarchical deep neural network is employed to achieve classification. Different from neural networks which are trained through a huge data set containing different angle combinations, our deep neural network can achieve DOA estimation of multiple sources with a small data set, since the classifiers can be trained in different small subregions. Simulation results demonstrate that the proposed method performs well both in generalization and imperfections adaptation.
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    • References (36)
  • [1]
    D. S. Talagala, W. Zhang, and T. D. Abhayapala,“Broadband doa estimation using sensor arrays on complex-shaped rigid bodies,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, no. 8, pp. 1573-1585, 2013. doi:10.1109/TASL.2013.2255282
    [2]
    M. Agrawal and S. Prasad,“Broadband DOA estimation using “spatial-only” modeling of array data,” IEEE Transactions on Signal Processing, vol. 48, no. 3, pp. 663-670, 2000. doi:10.1109/78.824662
    [3]
    R. Ma and N. Behdad,“Broadband, small-aperture direction-finding array with azimuth and elevation estimation capability,” IEEE Transactions on Antennas and Propagation, vol. 68, no. 4, pp. 3163-3175, 2020.
    [4]
    J. Duplouy, C. Morlaas, H. Aubert, Potier, Pouliguen, and C. Djoma,“Wideband and reconfigurable vector antenna using radiation pattern diversity for 3-d direction-of-arrival estimation,” IEEE Transactions on Antennas and Propagation, vol. 67, no. 6, pp. 3586-3596, 2019. doi:10.1109/TAP.2019.2905729
    [5]
    B. Liao, K. Tsui, and S. Chan,“Frequency invariant uniform concentric circular arrays with directional elements,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 2, pp. 871-884, 2013. doi:10.1109/TAES.2013.6494386
    [6]
    W. Liu, R. Wu, and R. J. Langley,“Design and analysis of broadband beamspace adaptive arrays,” IEEE Transactions on Antennas and Propagation, vol. 55, no. 12, pp. 3413-3420, 2007. doi:10.1109/TAP.2007.910322
    [7]
    Guaning Su and M. Morf,“The signal subspace approach for multiple wide-band emitter location,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 31, no. 6, pp. 1502-1522, 1983. doi:10.1109/TASSP.1983.1164233
    [8]
    G. Bienvenu, “Eigensystem properties of the sampled space correlation matrix, ” in ICASSP ’83. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 8, pp. 332–335, 1983.
    [9]
    M. Wax, Tie-Jun Shan, and T. Kailath,“Spatio-temporal spectral analysis by eigenstructure methods,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 32, no. 4, pp. 817-827, 1984. doi:10.1109/TASSP.1984.1164400
    [10]
    M. Allam and A. Moghaddamjoo,“Two-dimensional dft projection for wideband direction-of-arrival estimation,” IEEE Transactions on Signal Processing, vol. 43, no. 7, pp. 1728-1732, 1995. doi:10.1109/78.398738
    [11]
    H. Wang and M. Kaveh, “Estimation of angles-of-arrival for wideband sources, ” in ICASSP’84. IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 9, 1984, pp. 279–282.
    [12]
    S. Valaee and Kabal,“Wideband array processing using a two-sided correlation transformation,” IEEE Transactions on Signal Processing, vol. 43, no. 1, pp. 160-172, 1995. doi:10.1109/78.365295
    [13]
    H. Hung and M. Kaveh,“Focussing matrices for coherent signal-subspace processing,” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 36, no. 8, pp. 1272-1281, 1988. doi:10.1109/29.1655
    [14]
    M. A. Doron and A. J. Weiss,“On focusing matrices for wide-band array processing,” IEEE Transactions on Signal Processing, vol. 40, no. 6, pp. 1295-1302, 1992. doi:10.1109/78.139236
    [15]
    S. Valaee, B. Champagne, and Kabal,“Localization of wideband signals using least-squares and total least-squares approaches,” IEEE Transactions on Signal Processing, vol. 47, no. 5, pp. 1213-1222, 1999. doi:10.1109/78.757209
    [16]
    Ta-Sung Lee,“Efficient wideband source localization using beamforming invariance technique,” IEEE Transactions on Signal Processing, vol. 42, no. 6, pp. 1376-1387, 1994. doi:10.1109/78.286954
    [17]
    B. Liao and S. Chan,“Direction-of-arrival estimation in subarrays-based linear sparse arrays with gain/phase uncertainties,” IEEE Transactions on Aerospace and Electronic Systems, vol. 49, no. 4, pp. 2268-2280, 2013. doi:10.1109/TAES.2013.6621815
    [18]
    B. Liao, Z. G. Zhang, and S. C. Chan, “A subspace-based method for doa estimation of uniform linear array in the presence of mutual coupling, ” in 2010 IEEE International Symposium on Circuits and Systems (ISCAS), May 2010, pp. 1879–1882.
    [19]
    D. B. Ward, Zhi Ding, and R. A. Kennedy,“Broadband doa estimation using frequency invariant beamforming,” IEEE Transactions on Signal Processing, vol. 46, no. 5, pp. 1463-1469, 1998. doi:10.1109/78.668812
    [20]
    B. Friedlander and A. Weiss,“Direction finding in the presence of mutual coupling,” IEEE Transactions on Antennas and Propagation, vol. 39, no. 3, pp. 273-284, 1991. doi:10.1109/8.76322
    [21]
    B. C. Ng and C. M. S. See,“Sensor-array calibration using a maximum-likelihood approach,” IEEE Transactions on Antennas and Propagation, vol. 44, no. 6, pp. 827-835, 1996. doi:10.1109/8.509886
    [22]
    B. Liao and S. C. Chan,“Direction finding with partly calibrated uniform linear arrays,” IEEE Transactions on Antennas and Propagation, vol. 60, no. 2, pp. 922-929, 2012. doi:10.1109/TAP.2011.2173144
    [23]
    B. Liao, Z.-G. Zhang, and S.-C. Chan,“DOA estimation and tracking of ulas with mutual coupling,” IEEE Transactions on Aerospace and Electronic Systems, vol. 48, no. 1, pp. 891-905, 2012. doi:10.1109/TAES.2012.6129676
    [24]
    B. Liao, S.-C. Chan, L. Huang, and C. Guo,“Iterative methods for subspace and DOA estimation in nonuniform noise,” IEEE Transactions on Signal Processing, vol. 64, no. 12, pp. 3008-3020, 2016. doi:10.1109/TSP.2016.2537265
    [25]
    V. Vapnik, The nature of statistical learning theory. New York: Wiley, 1998.
    [26]
    Z. Liu, C. Zhang, and S. Yu,“Direction-of-arrival estimation based on deep neural networks with robustness to array imperfections,” IEEE Transactions on Antennas and Propagation, vol. 66, no. 12, pp. 7315-7327, 2018. doi:10.1109/TAP.2018.2874430
    [27]
    M. Pastorino and A. Randazzo,“A smart antenna system for direction of arrival estimation based on a support vector regression,” IEEE Transactions on Antennas and Propagation, vol. 53, no. 7, pp. 2161-2168, 2005. doi:10.1109/TAP.2005.850735
    [28]
    A. H. El Zooghby, C. G. Christodoulou, and M. Georgiopoulos,“A neural networkbased smart antenna for multiple source tracking,” IEEE Transactions on Antennas and Propagation, vol. 48, no. 5, pp. 768-776, 2000. doi:10.1109/8.855496
    [29]
    A. Randazzo, M. A. Abou-Khousa, M. Pastorino, and R. Zoughi,“Direction of arrival estimation based on support vector regression: Experimental validation and comparison with music,” IEEE Antennas and Wireless Propagation Letters, vol. 6, pp. 379-382, 2007. doi:10.1109/LAWP.2007.903491
    [30]
    T. Lo, H. Leung, and J. Litva,“Radial basis function neural network for direction-of-arrivals estimation,” IEEE Signal Processing Letters, vol. 1, no. 2, pp. 45-47, 1994. doi:10.1109/97.300315
    [31]
    M. Dehghanpour, V. T. Vakili, and A. Farrokhi, “DOA estimation using multiple kernel learning svm considering mutual coupling, ” in 2012 Fourth International Conference on Intelligent Networking and Collaborative Systems, Sep. 2012, pp. 55–61.
    [32]
    Ashok C and N. Venkateswaran, “Support vector regression based DOA estimation in heavy tailed noise environment, ” in 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), March 2016, pp. 99–102.
    [33]
    N. Venkateswaran and C. Ashok, “DOA estimation of near-field sources using support vector regression, ” in 2016 IEEE Region 10 Conference (TENCON), Nov 2016, pp. 1570–1574.
    [34]
    L. Wu and Z. Huang,“Coherent SVR learning for wideband direction-of-arrival estimation,” IEEE Signal Processing Letters, vol. 26, no. 4, pp. 642-646, 2019. doi:10.1109/LSP.2019.2901641
    [35]
    D. B. Ward, R. A. Kennedy, and R. C. Williamson,“Fir filter design for frequency invariant beamformers,” IEEE Signal Processing Letters, vol. 3, no. 3, pp. 69-71, 1996. doi:10.1109/97.481158
    [36]
    D. B. Ward, R. A. Kennedy, and R. C. Williamson,“Theory and design of broadband sensor arrays with frequency invariant far-field beam patterns,” Journal of the Acoustical Society of America, vol. 97, no. 2, pp. 1023-1034, 1995. doi:10.1121/1.412215
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