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Joint Estimation of Angle and Polarization for Bistatic MIMO Radar with Polarization Sensitive Array Using Dimension Reduction MUSIC

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Abstract

In this paper, we propose a new blind direction-of-departure (DOD), direction-of-arrival (DOA) and polarization estimation algorithm for bistatic polarimetric multiple-input multiple-output radar using dimension reduction multiple signal classification. The proposed algorithm obtains the initial estimation of DOD via the signal subspace, then utilizes one-dimension (1-D) local searching to estimate more accurate DOD according to the initial estimation of DOD, and finally joint estimates DOA and polarization by means of the receive polarization steering vector. The proposed algorithm, which convert multiple-dimension peak searching to 1-D local searching, can avoid the high computation cost. Simulation results show that the proposed algorithm has better angle and polarization parameter estimation performance than both estimation of signal parameters via rotational invariance technique algorithm and trilinear decomposition algorithm. Furthermore, the proposed algorithm can obtain automatically paired multi-dimensional parameter estimation.

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References

  1. Fishler, E., Haimovich, A., & Blum, R.S., et al. (2004). MIMO radar: An idea whose time has come. In Proceedings of IEEE radar conference (pp. 71–78).

  2. Wu, X. H., Kishk, A. A., & Glisson, A. W. (2010). MIMO-OFDM radar for direction estimation. IET Radar, Sonar & Navigation, 4(1), 28–36.

    Article  Google Scholar 

  3. Li, J., & Stoica, P. (2007). MIMO radar with colocated antennas. Signal Processing Magazine, IEEE, 24(5), 106–114.

    Article  Google Scholar 

  4. Li, J., Stoica, P., Xu, L., et al. (2007). On parameter identifiability of MIMO radar. IEEE Signal Processing Letters, 14(12), 968–971.

    Article  Google Scholar 

  5. Godrich, H., Haimovich, A. M., & Blum, R. S. (2010). Target localization accuracy gain in MIMO radar-based systems. IEEE Transactions on Information Theory, 56(6), 2783–2803.

    Article  MathSciNet  Google Scholar 

  6. Duofang, C., Baixiao, C., & Guodong, Q. (2008). Angle estimation using ESPRIT in MIMO radar. Electronics Letters, 44(12), 770–771.

    Article  Google Scholar 

  7. Chen, J. L., Gu, H., & Su, W. M. (2008). Angle estimation using ESPRIT without pairing in MIMI radar. Electronics Letters, 44(24), 1422–1423.

    Article  Google Scholar 

  8. Jin, M., Liao, G., & Li, J. (2009). Joint DOD and DOA estimation for bistatic MIMO radar. Signal Processing, 89(2), 244–251.

    Article  MATH  Google Scholar 

  9. Zhang, X., Xu, Z., Xu, L., et al. (2001). Trilinear decomposition-based transmit angle and receive angle estimation for multiple-input multiple-output radar. IET Radar, Sonar & Navigation, 5(6), 626–631.

    Article  Google Scholar 

  10. Nion, D., & Sidiropoulous, N. D. (2009). Adaptive algorithms to track the PARAFAC decomposition of a third-order tensor. IEEE Transactions on Signal Processing, 57(6), 2299–2310.

    Article  MathSciNet  Google Scholar 

  11. Gao, X., Zhang, X., Feng, G., et al. (2009). On the MUSIC-derived approaches of angle estimation for bistatic MIMO radar. In WNIS’09. International conference on wireless networks and information systems (pp. 343–346).

  12. Yan, H., Li, J., & Liao, G. (2008). Multitargey identification and localization using bistatic MIMO radar systems. EURASIP Journal on Advances in Signal Processing. Article ID283483, 1–8.

  13. Bencheikh, M.-L., & Wang, Y. (2010). Joint DOD–DOA estimation using combined ESPRIT–MUSIC approach in MIMO radar. Electronics Letters, 46(15), 1081–1083.

    Article  Google Scholar 

  14. Ng, J. W. P., & Manikas, A. (2005). Polarisation-sensitive array in blind MIMO CDMA system. Electronics Letters, 41(17), 49–50.

    Article  Google Scholar 

  15. Perez, J., Ibanez, J., Vielva, L., et al. (2004). Capacity estimation of polarization-diversity MIMO system in urban microcellular environments. In IEEE proceedings of the 15th international symposium on personal, indoor and mobile radio communications (Vol. 4, pp. 2730–2734).

  16. Ioannis, K., & Keith, G. B. (1994). Base station polarization-sensitive adaptive antenna for mobile radio. In Third annual international conference on universal personal communications (pp. 230–235).

  17. Deng, Y., Burr, A., & White, G. (2005). Performance of MIMO systems with combined polarization multiplexing and transmit diversity. In 2006 IEEE 61st vehicular technology conference. VTC 2005-Spring (vol. 2, pp. 869–873).

  18. Wong, K. T., & Zoltowski, M. D. (2000). Closed-form direction finding and polarization estimation with arbitrarily spaced electromagnetic vector-sensors at unknown locations. IEEE Transactions on Antennas and Propagation, 48(5), 671–680.

    Article  Google Scholar 

  19. Li, J., & Compton, R. T., Jr. (1992). Two-dimentional angle and polarization estimation using the ESPRIT Algorithm. IEEE Transactions on Antennas and Propagation, 40(5), 550–555.

  20. Jiang, H., Wang, D. F., & Liu, C. (2010). Joint estimation of DOD/DOA/polarization parameters of bistatic MIMO radar. The Journal of China Universities of Posts and Telecommunications, 17(5), 32–37.

    Article  Google Scholar 

  21. Jiang, H., Wang, D. F., & Liu, C. (2010). Estimation of DOD and 2D-DOA and polarizations for bistatic MIMO radar. In Wireless and optical communications conference (WOCC) 2010, May 14–15, Shanghai, China.

  22. Wang, K., Zhu, X., & He, J. (2012). Joint DOD DOA and polarization estimation for MIMO with electromagnetic vector sensor. Journal of Electronics & Information Technology, 34(1), 160–165.

    MATH  Google Scholar 

  23. Bencheikh, M. L., & Wang, Y. (2011). Combined esprit–rootmusic for DOA–DDD estimation in polarimetric bistatic MIMO radar. Progress in Electromagnetics Research Letters, 22, 109–117.

    Article  Google Scholar 

  24. Jiang, H., Zhang, Y., Li, J., et al. (2013). A PARAFAC-based algorithm for multidimensional parameter estimation in polarimetric bistatic MIMO radar. EURASIP Journal on Advances in Signal Processing, 2013(1), 1–14.

    Article  Google Scholar 

  25. Zheng, G., Yang, M., Chen, B., et al. (2012). Joint DOD/DOA and polarization estimation for interferometric MIMO radar with electromagnetic vector sensor. Journal of Electronics & Information Technology, 34(11), 2635–2641.

  26. Zhang, X., Xu, L., Xu, L., et al. (2010). Direction of departure (DOD) and direction of arrival (DOA) estimation in MIMO radar with reduced-dimension MUSIC. IEEE Communications Letters, 14(12), 1161–1163.

    Article  Google Scholar 

  27. Xu, Z., Wang, X., Xiao, S., et al. (2004). Filtering performance of polarization sensitive array: Completely polarized case. Acta Electronica Sinica, 32(8), 1310–1313.

    Google Scholar 

  28. Li, J. (1993). Direction and polarization estimation using arrays with small loops and short dipoles. IEEE Transactions on Antennas and Propagation, 41(3), 379–387.

    Article  Google Scholar 

  29. Zoltowski, M. D., & Wong, K. T. (2000). ESPRIT-based 2-D direction finding with a sparse uniform array of electromagnetic vector sensors. IEEE Transactions on Signal Processing, 48(8), 2195–2204.

    Article  Google Scholar 

  30. Stoica, P., & Nehorai, A. (1990). Performance study of conditional and unconditional direction-of-arrival estimation. IEEE Transactions on Signal Processing, 38(10), 1783–1795.

    Article  MATH  Google Scholar 

  31. Wax, M., & Kailath, T. (1985). Detection of the signals by information theoretic criteria. IEEE Transactions on ASSP, 33(2), 387–392.

    Article  MathSciNet  Google Scholar 

  32. Di, A. (1985). Multiple sources location—A matrix decomposition approach. IEEE Transactions on ASSP, 35(4), 1086–1091.

    Google Scholar 

  33. Shan, T. J., Paulray, A., & Kailath, T. (1987). On smoothed rand profile tests in eigen structure methods for direction-of-arrival estimation. IEEE Transactions on ASSP, 35(10), 1377–1385.

    Article  Google Scholar 

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Acknowledgments

This work is supported by China NSF Grants (61371169, 61071164), Jiangsu Planned Projects for Postdoctoral Research Funds (1201039C), China Postdoctoral Science Foundation (2012M521099, 2013M541661), Open project of key laboratory of underwater acoustic communication and marine information technology (Xiamen University), Hubei Key Laboratory of Intelligent Wire1ess Communications (IWC2012002), Open project of Key Laboratory of Nondestructive Testing (Nanchang Hangkong University), Open project of Key Laboratory of modern acoustic of Ministry of Education (Nanjing University), the Aeronautical Science Foundation of China(20120152001), Qing Lan Project and the Fundamental Research Funds for the Central Universities (NS2013024, NZ2012010, NZ2012012, kfjj130114).

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Correspondence to Ming Zhou.

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Zhou, M., Zhang, X. Joint Estimation of Angle and Polarization for Bistatic MIMO Radar with Polarization Sensitive Array Using Dimension Reduction MUSIC. Wireless Pers Commun 81, 1333–1345 (2015). https://doi.org/10.1007/s11277-014-2187-z

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