Adaptive beamforming with unknown scattering coefficients of near-field scatterers

Adaptive beamforming with unknown scattering coefficients of near-field scatterers

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Conventionally, near-field scattering effect was considered in antenna measurement, which requires a great amount of measuring efforts and re-measurement if the operational platform has changed. In this study, the authors consider the near-field scattering problem in the framework of adaptive array beamforming theory, which avoids re-measurement and can be adaptive to the arbitrary scenario. Generally, the near-field scattering can result in severe performance degradation in adaptive beamforming applications. They propose a robust adaptive beamforming approach that can maintain the performance in the presence of near-field scatterers with unknown scattering coefficients. In the authors’ approach, the near-field scatterering signal component is incorporated into the presumed steering vector. Thus, it is treated as useful information in this study instead of nuisance interference in the literature. In particular, the properties of the far-field direct-path signal and near-field signal are explored and the large uncertainty set is divided into two small ones describing the far-field and near-field steering vectors, respectively. Simulation examples are provided to show the performance improvement by making use of the near-field scattering signals.


    1. 1)
      • 1. Suresh-Babu, B.N., Torres, J.A., Guella, T.P.: ‘Impact of near-field scattering on multichannel airborne radar measurements (MCARM)’. Proc. IEEE National Radar Conf., Syracuse, NY, USA, May 1997, pp. 227231.
    2. 2)
      • 2. Naqvi, A., Yang, S.-T., Ling, H.: ‘Investigation of Doppler features from wind turbine scattering’, IEEE Antennas Wirel. Propag. Lett., 2010, 9, pp. 485488.
    3. 3)
      • 3. Capon, J.: ‘High-resolution frequency wavenumber spectrum analysis’, Proc. IEEE, 1969, 57, (8), pp. 14081418.
    4. 4)
      • 4. Vorobyov, S.A., Gershman, A.B., Luo, Z.Q.: ‘Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem’, IEEE Trans. Signal Process., 2003, 51, (2), pp. 313324.
    5. 5)
      • 5. Yang, L., McKay, M.R., Couillet, R.: ‘High-dimensional MVDR beamforming: optimized solutions based on spiked random matrix models’, IEEE Trans. Signal Process., 2018, 66, (7), pp. 19331947.
    6. 6)
      • 6. Carlson, B.D.: ‘Covariance matrix estimation errors and diagonal loading in adaptive arrays’, IEEE Trans. Aerosp. Electron. Syst., 1988, 24, (4), pp. 397401.
    7. 7)
      • 7. Cox, H., Zeskind, R.M., Owen, M.M.: ‘Robust adaptive beamforming’, IEEE Trans. Acoust. Speech Signal Process., 1987, 35, (10), pp. 13651376.
    8. 8)
      • 8. Wu, R., Bao, Z., Ma, Y.: ‘Control of peak sidelobe level in adaptive arrays’, IEEE Trans. Antennas Propag., 1996, 44, (10), pp. 13411347.
    9. 9)
      • 9. Forst, O.L.: ‘An algorithm for linearly constrained adaptive processing’, Proc. IEEE, 1972, 60, (8), pp. 926935.
    10. 10)
      • 10. Somasundaram, S.D.: ‘Linearly constrained robust capon beamforming’, IEEE Trans. Signal Process., 2012, 60, (11), pp. 58455856.
    11. 11)
      • 11. Xu, J., Zhu, S., Liao, G., et al: ‘Joint magnitude and phase constrained STAP approach’, Digit. Signal Process.,2015, 46, pp. 3240.
    12. 12)
      • 12. Xu, J., Liao, G., Zhu, S., et al: ‘Response vector constrained robust LCMV beamforming based on semidefinite programming’, IEEE Trans. Signal Process., 2015, 63, (21), pp. 57205732.
    13. 13)
      • 13. Li, Q., Liao, B., Huang, L., et al: ‘A robust STAP method for airborne radar with array steering vector mismatch’, Signal Process., 2016, 128, pp. 198203.
    14. 14)
      • 14. Li, J., Stoica, P., Wang, Z.: ‘On robust Capon beamforming and diagonal loading’, IEEE Trans. Signal Process., 2003, 51, (7), pp. 17021715.
    15. 15)
      • 15. Lorenz, R.G., Boyd, S.P.: ‘Robust minimum variance beamforming’, IEEE Trans. Signal Process., 2005, 53, (5), pp. 16841696.
    16. 16)
      • 16. Yu, H., Feng, D., Yao, X.: ‘Robust adaptive beamforming against large DOA mismatch with linear phase and magnitude constraints for multiple-input-multiple-output radar’, IET Signal Process., 2016, 10, (9), pp. 10621072.
    17. 17)
      • 17. Hassanien, A., Vorobyov, S.A., Wong, K.M.: ‘Robust adaptive beamforming using sequential programming: an iterative solution to the mismatch problem’, IEEE Signal Process. Lett., 2008, 15, pp. 733736.
    18. 18)
      • 18. Gu, Y., Amir, L.: ‘Robust adaptive beamforming based on interference covariance matrix reconstruction and steering vector estimation’, IEEE Trans. Signal Process., 2012, 60, (7), pp. 38813885.
    19. 19)
      • 19. Bucris, Y., Cohen, I., Doron, M.A.: ‘Bayesian focusing for coherent wideband beamforming’, IEEE Trans. Audio Speech Lang. Process., 2012, 20, (4), pp. 12821296.

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