Adaptive multiple-input multiple-output radar beamforming based on direct data domain approach

An adaptive multiple-input multiple-output (MIMO) radar beamforming technique based on direct data domain (D 3) approach is presented. The proposed method generally outperforms traditional adaptive beamformers in surprise or rapidly changing interference scenarios due to the use of a D 3 interference cancellation technique, which utilises a single snapshot for adaptive beamforming. The proposed D 3 approach suffers from performance degradation in the presence of uncertainty in the knowledge of target direction. To overcome this problem, a robust D 3 approach using worst-case performance optimisation is developed to achieve robustness against look direction error.

[1]  J. Capon High-resolution frequency-wavenumber spectrum analysis , 1969 .

[2]  I. Reed,et al.  Rapid Convergence Rate in Adaptive Arrays , 1974, IEEE Transactions on Aerospace and Electronic Systems.

[3]  M. O. Berin,et al.  Training and signal cancellation in adaptive radar , 1996, Proceedings of the 1996 IEEE National Radar Conference.

[4]  Alexander M. Haimovich,et al.  Signal cancellation effects in adaptive radar Mountaintop data-set , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[5]  William L. Melvin,et al.  Space-time adaptive radar performance in heterogeneous clutter , 2000, IEEE Trans. Aerosp. Electron. Syst..

[6]  Zhi-Quan Luo,et al.  Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem , 2003, IEEE Trans. Signal Process..

[7]  Jian Li,et al.  On robust Capon beamforming and diagonal loading , 2003, IEEE Trans. Signal Process..

[8]  Jian Li,et al.  Doubly constrained robust Capon beamformer , 2004, IEEE Transactions on Signal Processing.

[9]  Muralidhar Rangaswamy,et al.  Statistical analysis of the nonhomogeneity detector for non-Gaussian interference backgrounds , 2005, IEEE Transactions on Signal Processing.

[10]  Joseph Tabrikian,et al.  Transmission diversity smoothing for multi-target localization [radar/sonar systems] , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[11]  Alexander M. Haimovich,et al.  Spatial Diversity in Radars—Models and Detection Performance , 2006, IEEE Transactions on Signal Processing.

[12]  T.K. Sarkar,et al.  Adaptive processing using real weights based on a direct data domain least squares approach , 2006, IEEE Transactions on Antennas and Propagation.

[13]  Yuri I. Abramovich,et al.  Diagonally Loaded Normalised Sample Matrix Inversion (LNSMI) for Outlier-Resistant Adaptive Filtering , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[14]  Olivier Besson,et al.  Detection in the Presence of Surprise or Undernulled Interference , 2007, IEEE Signal Processing Letters.

[15]  Jian Li,et al.  On Parameter Identifiability of MIMO Radar , 2007, IEEE Signal Processing Letters.

[16]  L.J. Cimini,et al.  MIMO Radar with Widely Separated Antennas , 2008, IEEE Signal Processing Magazine.

[17]  Yuri I. Abramovich,et al.  Multiple-input multiple-output over-thehorizon radar: experimental results , 2009 .

[18]  Xiaofei Zhang,et al.  Trilinear decomposition-based transmit angle and receive angle estimation for multiple-input multiple-output radar , 2011 .

[19]  Lu Wang,et al.  Space-time adaptive monopulse processing for airborne radar in non-homogeneous environments , 2011 .

[20]  Wei Zhang,et al.  DOA estimation of coherent targets in MIMO radar , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[21]  Siliang Wu,et al.  Robust DOA estimation for a MIMO array using two calibrated transmit sensors , 2013 .