Skip to main content
SpringerLink
Log in

Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array

  • Short Paper
  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

In this paper, we employ the geometry of uniform circular array to achieve classification and localization of mixed near-field and far-field sources. Considering that the eigendecomposition of the covariance matrix requires high computational cost, we develop the propagator method to obtain the noise subspace and reduce complexity. Firstly, since the direction parameters of far-field sources at centrosymmetry sensors hold a conjugate structure while the covariance matrix of near-field sources holds a Hermitian structure, we exploit the covariance differencing approach to extract the pure near-field sources from mixed sources. Then, we improve the ESPRIT-like method and one-dimensional MUSIC method to determine the 2-D direction-of-arrival (DOA) and range of near-field sources, respectively. Finally, by calculating the noise power of mixed sources, we utilize the oblique projection approach to extract the pure far-field sources and exploit the 2-D MUSIC method to determine the 2-D DOA of far-field sources. Simulations demonstrate that the proposed algorithm can avoid the pseudo-peaks in the 2-D DOA spatial spectrum of far-field sources and provide the satisfactory performance of mixed source localization.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. H. Chen, W. Liu, W.-P. Zhu, M.N.S. Swamy, Q. Wang, Mixed rectilinear sources localization under unknown mutual coupling. J. Frankl. Inst. 356(4), 2372–2394 (2019)

    MathSciNet  MATH  Google Scholar 

  2. H. Chen, W. Wang, W. Liu, Joint DOA, range, and polarization estimation for rectilinear sources with a COLD array. IEEE Wirel. Commun. Lett. 8(5), 1398–1401 (2019)

    Google Scholar 

  3. H. Chen, W.-P. Zhu, W. Liu, M.N.S. Swamy, Y. Li, Q. Wang, Z. Peng, RARE-based localization for mixed near-field and far-field rectilinear sources. Digit. Signal Process. 85, 54–61 (2019)

    Google Scholar 

  4. X. Chen, Z. Liu, X. Wei, Unambiguous parameter estimation of multiple near-field sources via rotating uniform circular array. IEEE Antennas Wirel. Propag. Lett. 16, 872–875 (2017)

    Google Scholar 

  5. J. Delmas, H. Abeida, Stochastic Crame/spl acute/r-Rao bound for noncircular signals with application to DOA estimation. IEEE Trans. Signal Process. 52(11), 3192–3199 (2004)

    MathSciNet  MATH  Google Scholar 

  6. A.A. Ebrahimi, H.R. Abutalebi, M. Karimi, Generalised two stage cumulants-based MUSIC algorithm for passive mixed sources localisation. IET Signal Process. 13(4), 409–414 (2019)

    Google Scholar 

  7. E. Fishler, M. Grosmann, H. Messer, Detection of signals by information theoretic criteria: general asymptotic performance analysis. IEEE Trans. Signal Process. 50(5), 1027–1036 (2002)

    MathSciNet  MATH  Google Scholar 

  8. H. Gazzah, J.P. Delmas, CRB-based design of linear antenna arrays for near-field source localization. IEEE Trans. Antennas Propag. 62(4), 1965–1974 (2014)

    MathSciNet  MATH  Google Scholar 

  9. R. Goossens, H. Rogier, S. Werbrouck, UCA root-MUSIC with sparse uniform circular arrays. IEEE Trans. Signal Process. 56(8), 4095–4099 (2008)

    MathSciNet  MATH  Google Scholar 

  10. J. He, M.N.S. Swamy, M.O. Ahmad, Efficient application of MUSIC algorithm under the coexistence of far-field and near-field sources. IEEE Trans. Signal Process. 60(4), 2066–2070 (2012)

    MathSciNet  MATH  Google Scholar 

  11. J. He, Z. Zhang, C. Gu, T. Shu, W. Yu, Cumulant-based 2-D direction estimation using an acoustic vector sensor array. IEEE Trans. Aerosp. Electron. Syst. (2019). https://doi.org/10.1109/TAES.2019.2921194

    Article  Google Scholar 

  12. J. He, Z. Zhang, T. Shu, W. Yu, Direction finding of multiple partially polarized signals with a nested cross-Diople array. IEEE Antennas Wirel. Propag. Lett. 16, 1679–1682 (2017)

    Google Scholar 

  13. T. Jung, K. Lee, Closed-form algorithm for 3-D single-source localization with uniform circular array. IEEE Antennas Wirel. Propag. Lett. 13, 1096–1099 (2014)

    Google Scholar 

  14. G. Liu, X. Sun, Two-stage matrix differencing algorithm for mixed far-field and near-field sources classification and localization. IEEE Sens. J. 14(6), 1957–1965 (2014)

    Google Scholar 

  15. G. Liu, X. Sun, Spatial differencing method for mixed far-field and near-field sources localization. IEEE Signal Process. Lett. 21(11), 1331–1335 (2014)

    Google Scholar 

  16. M.L. McCloud, L.L. Scharf, A new subspace identification algorithm for high-resolution DOA estimation. IEEE Trans. Antennas Propag. 50(10), 1382–1390 (2002)

    MathSciNet  MATH  Google Scholar 

  17. A.M. Molaei, B. Zakeri, S.M.H. Andargoli, Passive localization and classification of mixed near-field and far-field sources based on high-order differencing algorithm. Signal Process. 157, 119–130 (2019)

    Google Scholar 

  18. J. Sanchez-Aranjo, S. Marcos, Statistical analysis of the propagator method for DOA estimation without eigendecomposition, in Proceedings of 8th Workshop on Statistical Signal and Array Processing (1996), pp. 570–573. https://doi.org/10.1109/SSAP.1996.534941

  19. X. Su, Z. Liu, X. Chen, X. Li, Mixed incoherent far-field and near-field source localization under uniform circular array. Sensors 18(5), 1432 (2018). https://doi.org/10.3390/s18051432

    Article  Google Scholar 

  20. X. Su, Z. Liu, T. Liu, B. Peng, X. Chen, X. Li, An SOS-based algorithm for localization of multiple near-field sources using uniform circular array. IEEE Sens. Lett. 3(11), 1–4 (2019)

    Google Scholar 

  21. K. Wang, L. Wang, J. Shang, X. Qu, Mixed near-field and far-field source localization based on uniform linear array partition. IEEE Sens. J. 16(22), 8083–8090 (2016)

    Google Scholar 

  22. F. Wen, Z. Zhang, G. Zhang, Y. Zhang, X. Wang, X. Zhang, A tensor-based covariance differencing method for direction estimation in bistatic MIMO radar with unknown spatial colored noise. IEEE Access 5, 18451–18458 (2017)

    Google Scholar 

  23. Y. Wu, H. Wang, Y. Zhang, Y. Wang, Multiple near-field source localisation with uniform circular array. Electron. Lett. 49(24), 1509–1510 (2013)

    Google Scholar 

  24. J. Xie, H. Tao, X. Rao, J. Su, Passive localization of mixed far-field and near-field sources without estimating the number of sources. Sensors 15(2), 3834–3853 (2015)

    Google Scholar 

  25. J. Xie, H. Tao, X. Rao, J. Su, Localization of mixed far-field and near-field sources under unknown mutual coupling. Digit. Signal Process. 50, 229–239 (2016)

    Google Scholar 

  26. B. Xue, G. Fang, Y. Ji, Passive localisation of mixed far-field and near-field sources using uniform circular array. Electron. Lett. 52(20), 1690–1692 (2016)

    Google Scholar 

  27. N. Yuen, B. Friedlander, Performance analysis of higher order ESPRIT for localization of near-field sources. IEEE Trans. Signal Process. 46(3), 709–719 (1998)

    Google Scholar 

  28. Z. Zheng, M. Fu, D. Jiang, W. Wang, S. Zhang, Localization of mixed far-field and near-field sources via cumulant matrix reconstruction. IEEE Sens. J. 18(18), 7671–7680 (2018)

    Google Scholar 

  29. Z. Zheng, M. Fu, W. Wang, S. Zhang, Y. Liao, Localization of mixed near-field and far-field sources using symmetric double-nested arrays. IEEE Trans. Antennas Propag. 67(11), 7059–7070 (2019)

    Google Scholar 

  30. Z. Zheng, M. Fu, W.-Q. Wang, H.C. So, Signal processing mixed far-field and near-field source localization based on subarray cross-cumulant. Signal Process. 150, 51–56 (2018)

    Google Scholar 

  31. Z. Zheng, G. Li, Y. Teng, 2D DOA estimator for multiple coherently distributed sources using modified propagator. Circuits Syst. Signal Process. 31(1), 255–270 (2012)

    MathSciNet  MATH  Google Scholar 

  32. Z. Zheng, J. Sun, W.-Q. Wang, H. Yang, Classification and localization of mixed near-field and far-field sources using mixed-order statistics. Signal Process. 143, 134–139 (2018)

    Google Scholar 

  33. W. Zhi, M.Y. Chia, Near-field source localization via symmetric subarrays. IEEE Signal Process. Lett. 14(6), 409–412 (2007)

    Google Scholar 

  34. W. Zuo, J. Xin, W. Liu, N. Zheng, H. Ohmori, A. Sano, Localization of near-field sources based on linear prediction and oblique projection operator. IEEE Trans. Signal Process. 67(2), 415–430 (2019)

    MathSciNet  MATH  Google Scholar 

  35. W. Zuo, J. Xin, N. Zheng, A. Sano, Subspace-based localization of far-field and near-field signals without eigendecomposition. IEEE Trans. Signal Process. 66(17), 4461–4476 (2018)

    MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by the Natural Science Foundation of China Hunan Province under Grant 2017JJ3368.

Author information

Authors and Affiliations

  1. College of Electronic Science and Technology, National University of Defense Technology, Changsha, 410073, China

    Xiaolong Su, Zhen Liu, Tianpeng Liu, Bo Peng, Xin Chen & Xiang Li

Authors
  1. Xiaolong Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tianpeng Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bo Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhen Liu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Su, X., Liu, Z., Liu, T. et al. Passive Localization of Mixed Near-Field and Far-Field Sources Without Eigendecomposition via Uniform Circular Array. Circuits Syst Signal Process 39, 5298–5317 (2020). https://doi.org/10.1007/s00034-020-01413-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-020-01413-x

Keywords

Search

Navigation