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Near-Field DOA-Range and Polarization Estimation Based on Exact Propagation Model with COLD Arrays

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Abstract

Many existing near-field source localization algorithms assume simplified models, for example, the Fresnel approximation model. Unlike these works, a new algorithm is herein proposed to localize multiple near-field electromagnetic sources under the exact source-array propagation model. Using the data measured by a linear (not necessarily uniform) cocentered orthogonal loop and dipole (COLD) array, three cumulant matrices are firstly defined to construct two matrix pencils. The magnitudes of the two matrix pencils’ generalized eigenvalues are then combined with their phases to extract the direction-of-arrival (DOA) and range estimates of the sources. The key idea of the new algorithm is to use a set of coarse estimates obtained from the magnitudes to resolve the set of ambiguous estimates obtained from the phases. In addition, the proposed algorithm estimates the polarizations without needing the prior estimation of the DOA-range parameters. This proposed algorithm is analytic, requires no iterative computations, and does not need to confine the inter-element spacing to be within a quarter wavelength.

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Data Availability Statement

The data used to support the findings of this study are available from the corresponding author upon request.

References

  1. E. Boyer, A. Ferreol, P. Larzabal, Simple robust bearing-range source’s localization with curved wavefronts. IEEE Signal Process. Lett. 12(6), 457–460 (2005)

    Article  Google Scholar 

  2. J.C. Chen, R.E. Hudson, K. Yao, Maximum-likelihood source localization and unknown sensor location estimation for wideband signals in the near-field. IEEE Trans. Signal Process. 50(8), 1843–1854 (2002)

    Article  Google Scholar 

  3. 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)

    Article  Google Scholar 

  4. J.P. Delmas, M.N.E. Korso, H. Gazzah, M. Castella, CRB analysis of planar antenna arrays for optimizing near-field source localization. Signal Process. 127, 117–134 (2016)

    Article  Google Scholar 

  5. M.C. Dogan, J.M. Mendel, Applications of cumulants to array processing. Part I: aperture extension and array calibration. IEEE Trans. Signal Process. 43(5), 1200–1216 (1995)

  6. B. Friedlander, Localization of signals in the near-field of an antenna array. IEEE Trans. Signal Process. 67(15), 3885–3893 (2019)

    Article  Google Scholar 

  7. E. Grosicki, K. Abed-Meraim, Y. Hua, A weighted linear prediction method for near-field source localization. IEEE Trans. Signal Process. 53(10), 3651–3660 (2005)

    Article  MathSciNet  Google Scholar 

  8. C. Guanghui, Z. Xiaoping, J. Shuang, Y. Anning, L. Qi, High accuracy near-field localization algorithm at low SNR using fourth-order cumulant. IEEE Commun. Lett. 24(3), 553–557 (2020)

    Article  Google Scholar 

  9. J. He, M.O. Ahmad, M.N.S. Swamy, Extended-aperture angle-range estimation of multiple Fresnel-region sources with a linear tripole array using cumulants. Signal Process. 92(4), 939–953 (2012)

    Article  Google Scholar 

  10. J. He, M.O. Ahmad, M.N.S. Swamy, Near-field localization of partially polarized sources with a cross-dipole array. IEEE Trans. Aerosp. Electron. Syst. 49(2), 857–870 (2013)

    Article  Google Scholar 

  11. J. He, L. Li, T. Shu, Near-field parameter estimation for polarized source using spatial amplitude ratio. IEEE Commun. Lett. 24(9), 1961–1965 (2020)

    Article  Google Scholar 

  12. J. He, L. Li, T. Shu, Localization of near-field sources for exact source-sensor spatial geometry. IEEE Signal Process. Lett. 27, 1040–1044 (2020)

    Article  Google Scholar 

  13. J. He, L. Li, T. Shu, T.-K. Truong, Mixed near-field and far-field source localization based on exact spatial propagation geometry. IEEE Trans. Veh. Technol. 70(4), 3540–3551 (2021)

    Article  Google Scholar 

  14. Y. Hsu, K.T. Wong, L. Yeh, Mismatch of near-field bearing range spatial geometry in source-localization by a uniform linear array. IEEE Trans. Antennas Propag. 59(10), 3658–3667 (2011)

    Article  Google Scholar 

  15. Y.D. Huang, M. Barkat, Near-field multiple source localization by passive sensor array. IEEE Trans. Antennas Propag. 39(7), 968–975 (1991)

    Article  Google Scholar 

  16. D.H. Johnson, D.E. Dudgeon, Array Signal Processing: Concepts and Techniques (Prentice-Hall, Upper Saddle River, NJ, USA, 1993)

    MATH  Google Scholar 

  17. H. Krim, M. Viberg, Two decades of array signal processing research: the parametric approach. IEEE Signal Process. Mag. 13(4), 67–94 (1996)

    Article  Google Scholar 

  18. J. Li, P. Stoica, D. Zheng, Efficient direction and polarization estimation with a COLD array. IEEE Trans. Antennas Propag. 44(4), 539–547 (1996)

    Article  Google Scholar 

  19. X. Li, Q. Gong, S. Zhong, S. Ren, Near-field noncircular sources localization based on fourth-order cumulant. IEEE Access 8, 120575–120585 (2020)

    Article  Google Scholar 

  20. J. Li, Y. Wang, Z. Ren, X. Gu, M. Yin, Z. Wu, DOA and range estimation using a uniform linear antenna array without a priori knowledge of the source number. IEEE Trans. Antennas Propag. 69(5), 2929–2939 (2021)

    Article  Google Scholar 

  21. J. Liang, D. Liu, Passive localization of near-field sources using cumulant. IEEE Sensors J. 9(8), 953–960 (2009)

    Article  Google Scholar 

  22. S. Pasupathy, W.J. Alford, Range and bearing estimation in passive sonar. IEEE Trans. Aerosp. Electron. Syst. 16(2), 244–249 (1980)

    Article  Google Scholar 

  23. R. Roy, T. Kailath, ESPRIT-estimation of signal parameters via rotational invariance techniques. IEEE Trans. Acoust. Speech Signal Process. 37(7), 984–995 (1989)

    Article  Google Scholar 

  24. T. Shu, L. Li, J. He, Near-field localization for non-circular sources in the presence of sensor phase uncertainties. IEEE Wireless Commun. Lett. 10(3), 562–566 (2021)

    Article  Google Scholar 

  25. T. Shu, J. He, L. Li, Near-field passive localization and gain-phase compensation with partly calibrated arrays. IEEE Trans. Aerosp. Electron. Syst. 58(1), 712–719 (2022)

    Article  Google Scholar 

  26. T. Shu, J. He, V. Dakulagi, 3-D near-field source localization using a spatially spread acoustic vector sensor. IEEE Trans. Aerosp. Electron. Syst. 58(1), 180–188 (2022)

    Article  Google Scholar 

  27. J. Tao, L. Liu, Z. Lin, Joint DOA, range, and polarization estimation in the fresnel region. IEEE Trans. Aerosp. Electron. Syst. 47(4), 2657–2672 (2011)

    Article  Google Scholar 

  28. H.L. Van Trees, Optimum array processing, part IV of detection, estimation, and modulation theory (Wiley, New York, NY, USA, 2002)

    Google Scholar 

  29. A.J. van der Veen, P.B. Ober, E.F. Deprettere, Azimuth and elevation computation in high resolution DOA estimation. IEEE Trans. Signal Process. 40(7), 1828–1833 (1992)

    Article  Google Scholar 

  30. M. Wax, T. Kailath, Detection of signals by information theoretic criteria. IEEE Trans. Acoust. Speech Signal Process. 33(4), 387–392 (1985)

    Article  MathSciNet  Google Scholar 

  31. A.J. Weiss, B. Friedlander, Range and bearing estimation using polynomial rooting. IEEE J. Ocean. Eng. 18(2), 130–137 (1993)

    Article  Google Scholar 

  32. Y. Wu, L. Ma, C. Hou, G. Zhang, J. Li, Subspace-based method for joint range and DOA estimation of multiple near-field sources. Signal Process. 86(8), 2129–2133 (2006)

    Article  Google Scholar 

  33. Y. Wu, H.C. So, C. Hou, J. Li, Passive localization of near-field sources with a polarization sensitive array. IEEE Trans. Antennas Propag. 55(8), 2402–2408 (2007)

    Article  Google Scholar 

  34. J. Xu, B. Wang, F. Hu, Near-field sources localization in partly calibrated sensor arrays with unknown gains and phases. IEEE Wirel. Commun. Lett. 8(1), 89–92 (2019)

    Article  Google Scholar 

  35. 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)

    Article  Google Scholar 

  36. X. Zhang, W. Chen, W. Zheng, Z. Xia, Y. Wang, Localization of near-field sources: a reduced-dimension MUSIC algorithm. IEEE Commun. Lett. 22(7), 1422–1425 (2018)

    Article  Google Scholar 

  37. T. Zhao, Z. Zhang, H. Chen, L. Qi, W. Liu, Augmented quaternion MUSIC method for near-field noncircular sources with a COLD array. IEEE Access 8, 212106–212113 (2020)

    Article  Google Scholar 

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

    Article  Google Scholar 

  39. 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)

    Article  MathSciNet  Google Scholar 

  40. W. Zuo, J. Xin, N. Zheng, H. Ohmori, A. Sano, Subspace based near-field source localization in unknown spatially nonuniform noise environment. IEEE Trans. Signal Process. 68, 4713–4726 (2020)

    Article  Google Scholar 

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Appendix A: Derivations of Eqs. (15)–(17)

Appendix A: Derivations of Eqs. (15)–(17)

Let \({\varvec{C}}_1(j, \ell )\) be the \((j, \ell )\)th entry of \({\varvec{C}}_1\). Then, \({\varvec{C}}_1(j, \ell )\) can be expressed as

$$\begin{aligned} {\varvec{C}}_1(j, \ell )= & {} \sum _{i = 1}^2 \left\{ \mathrm{cum} \left[ \sum _{k = 1}^K a_{1,k} c_{i,k} s_k(t), \sum _{k = 1}^K a_{1,k}^*c_{i,k}^*s_k^*(t) \sum _{k = 1}^K b_{j,k} s_k(t) \sum _{k = 1}^K b_{\ell ,k}^*s_k^*(t) \right] \right\} \nonumber \\= & {} \sum _{i = 1}^2 \left\{ \left[ \sum _{k = 1}^K (a_{1,k} c_{i,k} a_{1,k}^*c_{i,k}^*b_{j,k} b_{\ell ,k}^*) \times \mathrm{cum}[s_k(t), s_k^*(t), s_k(t), s_k^*(t)]\right] \right\} \nonumber \\= & {} \sum _{k = 1}^K b_{j,k} b_{\ell ,k}^*\rho _k \end{aligned}$$
(41)

where \(a_{m,k} = a_{m}(\theta _k, r_k)\) and \(b_{j, k}\) is the (jk)th entry of \({\varvec{B}}\). In establishing (41), the fact that \(c_{1,k} c_{1,k}^*+ c_{2,k} c_{2,k}^*= 1\), \(\forall k\), is used. Expressing \({\varvec{C}}_1(j, \ell )\) for all \(j, \ell = 1, \ldots , 2M\) in matrix form, Eq. (15) is established.

Similarly, the \((j, \ell )\)th entries of \({\varvec{C}}_2(j, \ell )\) and \({\varvec{C}}_3(j, \ell )\) can be expressed, respectively, as

$$\begin{aligned} {\varvec{C}}_2(j, \ell ) = \sum _{k = 1}^K b_{j,k} b_{\ell ,k}^*a_{p,k} \rho _k \end{aligned}$$
(42)

and

$$\begin{aligned} {\varvec{C}}_3(j, \ell ) = \sum _{k = 1}^K b_{j,k} b_{\ell ,k}^*a_{q,k} \rho _k \end{aligned}$$
(43)

For all \(j, \ell = 1, \ldots , 2M\), \(p \in [1, M]\), and \(q \in [1, M]\), Eq. (42) yields (16) and eq. (43) yields (17).

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Yin, K., Dai, Y. & Gao, C. Near-Field DOA-Range and Polarization Estimation Based on Exact Propagation Model with COLD Arrays. Circuits Syst Signal Process 41, 5183–5200 (2022). https://doi.org/10.1007/s00034-022-02029-z

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