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2022-08-01
Projection Constraint Null Broadening and Deepening Method for Conjugate Array
By
Progress In Electromagnetics Research Letters, Vol. 105, 121-129, 2022
Abstract
The performance of the Capon beamforming sharply decreases against strong directional and large deviation interference. In order to reduce the impact of the abnormal interference, this paper proposes a large degree of freedom null broadening beamforming for non-circular signals. The signal vector is first extended by a uniform linear conjugate array. The covariance matrix of the array is then reconstructed by projection transformation and diagonal loading technique. Finally, the beamforming is constrained by the characteristic subspace of the guide vector matrix, and the analytic expression of the optimal weights of the method is derived. The numerical simulations demonstrate that the proposed null broadening method has the advantages of high degrees of freedom and strong parameter selection robustness.
Citation
Shi-Jing Xiao, Bin Li, and Qing Wang, "Projection Constraint Null Broadening and Deepening Method for Conjugate Array," Progress In Electromagnetics Research Letters, Vol. 105, 121-129, 2022.
doi:10.2528/PIERL22051103
References

1. Jian, L. and S. Petre, Robust Adaptive Beamforming, John Wiley & Sons, Inc., 2005.

2. Chen, X., T. Shu, K.-B. Yu, J. He, and W. Yu, "Joint adaptive beamforming techniques for distributed array radars in multiple mainlobe and sidelobe jammings," IEEE Antennas and Wireless Propagation Letters, Vol. 19, No. 2, 248-252, 2019.
doi:10.1109/LAWP.2019.2958687

3. Chen, X., et al. "Magnetic metamirrors as spatial frequency filters," IEEE Transactions on Antennas and Propagation, Vol. 68, No. 7, 5505-5511, 2020.
doi:10.1109/TAP.2020.2977736

4. Sohrabi, F., Z. Chen, and W. Yu, "Deep active learning approach to adaptive beamforming for mmwave initial alignment," IEEE Journal on Selected Areas in Communications, Vol. 39, No. 8, 2347-2360, 2021.
doi:10.1109/JSAC.2021.3087234

5. Bi, Y., "Robust adaptive beamforming based on interference-plus-noise covariance matrix reconstruction method," Progress In Electromagnetics Research M, Vol. 97, 87-96, 2020.
doi:10.2528/PIERM20082003

6. Zhang, M., A. Zhang, and Q. Yang, "Robust adaptive beamforming based on conjugate gradient algorithms," IEEE Transactions on Signal Processing, Vol. 64, No. 22, 6046-6057, 2016.
doi:10.1109/TSP.2016.2605075

7. Huang, Y., S. A. Vorobyov, and Z.-Q. Luo, "Quadratic matrix inequality approach to robust adaptive beamforming for general-rank signal model," IEEE Transactions on Signal Processing, Vol. 68, 2244-2255, 2020.
doi:10.1109/TSP.2020.2981208

8. Salvati, D., C. Drioli, and G. L. Foresti, "A low-complexity robust beamforming using diagonal unloading for acoustic source localization," IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 26, No. 3, 609-622, 2018.
doi:10.1109/TASLP.2017.2789321

9. Yang, H., P. Wang, and Z. Ye, "Robust adaptive beamforming via covariance matrix reconstruction under colored noise," IEEE Signal Processing Letters, Vol. 28, 1759-1763, 2021.
doi:10.1109/LSP.2021.3105930

10. Guerci, J. R., "Theory and application of covariance matrix tapers for robust adaptive beamforming," IEEE Transactions on Signal Processing, Vol. 47, No. 4, 977-985, 1999.
doi:10.1109/78.752596

11. Pajovic, M., J. C. Preisig, and A. B. Baggeroer, "Analysis of optimal diagonal loading for MPDR-based spatial power estimators in the snapshot deficient regime," IEEE Journal of Oceanic Engineering, Vol. 44, No. 2, 451-465, 2018.
doi:10.1109/JOE.2018.2815480

12. Pan, C., J. Benesty, and J. Chen, "Design of directivity patterns with a unique null of maximum multiplicity," IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 24, No. 2, 226-235, 2015.
doi:10.1109/TASLP.2015.2504866

13. Ors, B. and R. Suleesathira, "First and second order iterative null broadening beamforming," 2019 3rd International Conference on Imaging, Signal Processing and Communication (ICISPC), 47-51, 2019, IEEE.
doi:10.1109/ICISPC.2019.8935850

14. Landon, J., B. D. Jeffs, and K. F. Warnick, "Model-based subspace projection beamforming for deep interference nulling," IEEE Transactions on Signal Processing, Vol. 60, No. 3, 1215-1228, 2011.
doi:10.1109/TSP.2011.2177825

15. Somasundaram, S. D., "Linearly constrained robust Capon beamforming," IEEE Transactions on Signal Processing, Vol. 60, No. 11, 5845-5856, 2012.
doi:10.1109/TSP.2012.2212889

16. Li, S. and X.-P. Zhang, "Dilated arrays: A family of sparse arrays with increased uniform degrees of freedom and reduced mutual coupling on a moving platform," IEEE Transactions on Signal Processing, Vol. 69, 3367-3382, 2021.
doi:10.1109/TSP.2021.3083988

17. Li, J., J. Zhao, Y. Ding, Y. Li, and F. Chen, "An improved co-prime parallel array with conjugate augmentation for 2-D DOA estimation," IEEE Sensors Journal, Vol. 21, No. 20, 23400-23411, 2021.
doi:10.1109/JSEN.2021.3106382

18. Song, J., F. Shen, and J. Shen, "Sparse array design exploiting the augmented conjugate correlation statistics for DOA estimation," IEEE Access, Vol. 8, 41951-41960, 2020.
doi:10.1109/ACCESS.2020.2976570

19. Shaw, A., J. Smith, and A. Hassanien, "MVDR beamformer design by imposing unit circle roots constraints for uniform linear arrays," IEEE Transactions on Signal Processing, Vol. 69, 6116-6130, 2021.
doi:10.1109/TSP.2021.3121630

20. Wax, M. and A. Adler, "Subspace-constrained array response estimation in the presence of model errors," IEEE Transactions on Signal Processing, Vol. 69, 417-427, 2020.

21. Wax, M. and A. Adler, "Detection of the number of signals by signal subspace matching," IEEE Transactions on Signal Processing, Vol. 69, 973-985, 2021.
doi:10.1109/TSP.2021.3053495

22. Zheng, Z., W.-Q. Wang, Y. Kong, and Y. D. Zhang, "MISC array: A new sparse array design achieving increased degrees of freedom and reduced mutual coupling effect," IEEE Transactions on Signal Processing, Vol. 67, No. 7, 1728-1741, 2019.
doi:10.1109/TSP.2019.2897954