volume | PIER Journals

Abstract

Space-time adaptive antijamming problem has received significant attention recently for global navigation satellite system (GNSS). It can jointly utilize spatial filters and temporal filters to suppress interference signals. However, most of the works on space-time antijamming problem presented in the literature require a space-time two-dimension (2-D) array with multiple antennas and delay taps. In this paper, an effective adaptive antijamming method based on space-time a 2-D sparse array is proposed. The maximum array gain is utilized to construct a space-time 2-D sparse array. The space-time antijamming weight vector is given by minimizing the 2-D sparse array output power. Compared with the previous works, the presented method can have better antijamming performance than a space-time 2-D uniform array. Simulation results verify the effectiveness and feasibility of the proposed method.

1. Souden, M., J. Benesty, and S. Affes, "A study of the LCMV and MVDR noise reduction filters," IEEE Transactions on Signal Processing, Vol. 58, No. 9, 4925-4935, 2010.
doi:10.1109/TSP.2010.2051803 Google Scholar

2. Huang, Y. W., M. K. Zhou, and S. A. Vorobyov, "New designs on MVDR robust adaptive beamforming based on optimal steering vector estimation," IEEE Transactions on Signal Processing, Vol. 67, No. 14, 3624-3638, 2019.
doi:10.1109/TSP.2019.2918997 Google Scholar

3. Saeed, M. and K. Osman, "Adaptive beamforming based on theoretical interference-plus-noise covariance and direction-of-arrival estimation," IET Signal Processing, Vol. 12, No. 10, 819-825, 2018. Google Scholar

4. Donelli, M. and P. Febvre, "An inexpensive reconfigurable planar array for Wi-Fi applications," Progress In Electromagnetics Research C, Vol. 28, 71-81, 2012.
doi:10.2528/PIERC12012304 Google Scholar

5. Chen, F. Q., J. W. Nie, B. Y. Li, and F. X. Wang, "Distortionless space-time adaptive processor for global navigation satellite system receiver," Electronics Letters, Vol. 51, No. 25, 2138-2139, 2015.
doi:10.1049/el.2015.2832 Google Scholar

6. Lu, Z. K., J. W. Nie, F. Q. Chen, H. M. Chen, and G. Ou, "Adaptive time taps of STAP under channel mismatch for GNSS antenna arrays," IEEE Transactions on Instrumentation and Measurement, Vol. 66, No. 11, 2813-2824, 2017.
doi:10.1109/TIM.2017.2728420 Google Scholar

7. Saeed, D., J. Ali, B. Ali, and L. Grard, "GNSS space-time interference mitigation and attitude determination in the presence of interference signals," Sensors, Vol. 15, No. 6, 12180-12204, 2015.
doi:10.3390/s150612180 Google Scholar

8. Dai, X. Z., J. W. Nie, F. Q. Chen, and G. Ou, "Distortionless space-time adaptive processor based on MVDR beamformer for GNSS receiver," IET Radar Sonar & Navigation, Vol. 11, No. 10, 1488-1494, 2017.
doi:10.1049/iet-rsn.2017.0168 Google Scholar

9. Liu, F., R. Du, and X. Bai, "A virtual space-time adaptive beamforming method for space-time antijamming," Progress In Electromagnetics Research M, Vol. 58, 183-191, 2017.
doi:10.2528/PIERM17050304 Google Scholar

10. Xu, J. W., G. S. Liao, S. Q. Zhu, and L. Huang, "Response vector constrained robust LCMV beamforming based on semidefinite programming," IEEE Transactions on Signal Processing, Vol. 63, No. 21, 5720-5732, 2015.
doi:10.1109/TSP.2015.2460221 Google Scholar

11. Zheng, Z., W. Q. Wang, Y. 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 Google Scholar

12. Muran, G., Y. D. Zhang, and T. Chen, "DOA estimation using compressed sparse array," IEEE Transactions on Signal Processing, Vol. 66, No. 15, 4133-4146, 2018.
doi:10.1109/TSP.2018.2847645 Google Scholar

13. Hu, B., X. C. Wu, X. Zhang, Q. Yang, and W. B. Deng, "Adaptive beamforming for sparse array based on semi-definite programming," IEEE Access, Vol. 6, 64525-64532, 2018.
doi:10.1109/ACCESS.2018.2878153 Google Scholar

14. Hawes, M. B. and W. Liu, "Sparse array design for wideband beamforming with reduced complexity in tapped delay-lines," IEEE/ACM Transactions on Audio Speech and Language Processing, Vol. 22, No. 88, 1236-1247, 2014.
doi:10.1109/TASLP.2014.2327298 Google Scholar

15. Amin, M. G., X. R. Wang, Y. D. Zhang, and F. Ahmad, "Sparse arrays and sampling for interference mitigation and DOA estimation in GNSS," Proceedings of the IEEE, Vol. 104, No. 6, 1302-1317, 2016.
doi:10.1109/JPROC.2016.2531582 Google Scholar

16. Donelli, M., T. Moriyama, and M. Manekiya, "A compact switched-beam planar antenna array for wireless sensors operating at Wi-Fi band," Progress In Electromagnetics Research C, Vol. 83, 137-145, 2018.
doi:10.2528/PIERC18012004 Google Scholar

17. Wang, X. R., M. Amin, and X. Cao, "Analysis and design of optimum sparse array configurations for adaptive beamforming," IEEE Transactions on Signal Processing, Vol. 66, No. 2, 340-351, 2017.
doi:10.1109/TSP.2017.2760279 Google Scholar

18. Wang, X. R., M. Amin, and X. H. Wang, "Robust sparse array design for adaptive beamforming against DOA mismatch," Signal Processing, Vol. 146, 41-49, 2018.
doi:10.1016/j.sigpro.2017.12.018 Google Scholar

19. Meyer, C., "Matrix analysis and applied linear algebra," Society for Industrial and Applied Mathematics, 2000. Google Scholar

20. Horst, R. and P. M. Pardalos, Introduction to Global Optimization, Springer-Verlag New York, Inc., 2002.

21. Fazel, M., H. Hindi, and S. P. Boyd, "Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices," American Control Conference, Vol. 3, 2156-2162, 2003. Google Scholar

22. Grant, M., CVX: Matlab software for disciplined convex programming, Version 1.21, 2008.

Dr. Ruiyan Du

Prof. Fulai Liu

Dr. Kai Tang

Dr. Hui Song