Vol. 99

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues
2020-12-15

RRT-MWF-MVDR Algorithm for Space-Time Antijamming

By Fulai Liu, Ruiyan Du, and Hui Song
Progress In Electromagnetics Research M, Vol. 99, 201-210, 2021
doi:10.2528/PIERM20081301

Abstract

Minimum variance distortionless response (MVDR) beamformer is an one of the well-known space-time antijamming techniques for global navigation satellite system (GNSS). It can jointly utilize spatial filter and temporal filter to suppress interference signals. However, the computational complexity is usually so high that it is difficult to apply in engineering problems. In order to solve this problem, a novel MVDR algorithm based on rank-reducing transformation (RRT) and multistage wiener filter (MWF) is proposed for reducing the computational complexity, named as RRT-MWF-MVDR algorithm. Via the characteristics of the oppressive jamming environment and the steering vector of satellite signal, a rank-reducing transformation is given. By the rank-reducing transformation, a rank reduction is realized for the high dimensional received data. Taking these received data with reduced rank as the input of the MWF, the forward decomposition and backward iteration are accomplished. Then the equivalent reduced rank matrix and equivalent weight vector of MWF can be given, respectively. Finally, the space-time two-dimensional antijamming weight vector is given by the mathematical relationship between the reduced-rank matrix and the weight vector.The proposed method can effectively avoid the inverse of high-dimensional matrix. The proposed method offers a number of advantages over the existing algorithms. For example, (1) it has less computational load and is easier to be executed in practical application. (2) It can maintain higher output signal-to-interference-noise ratio (SINR). Simulation results verify the effectiveness of proposed method.

Citation


Fulai Liu, Ruiyan Du, and Hui Song, "RRT-MWF-MVDR Algorithm for Space-Time Antijamming," Progress In Electromagnetics Research M, Vol. 99, 201-210, 2021.
doi:10.2528/PIERM20081301
http://www.jpier.org/PIERM/pier.php?paper=20081301

References


    1. Hu, H. and N. Wei, "A study of GPS jamming and anti-jamming," International Conference on Power Electronics & Intelligent Transportation System, 2010.

    2. 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

    3. 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

    4. Tufts, D. W., R. Kumaresan, and I. Kirsteins, "Data adaptive signal estimation by singular value decomposition of a data matrix," Proceedings of the IEEE, Vol. 70, No. 6, 684-685, 1982.
    doi:10.1109/PROC.1982.12367

    5. Goldstein, J. S. and I. S. Reed, "Reduced-rank adaptive filtering," IEEE Transactions on Signal Processing, Vol. 45, No. 2, 492-496, 1997.
    doi:10.1109/78.554317

    6. Goldstein, J. S., I. S. Reed, and L. L. Scharf, "A multistage representation of the Wiener filter based on orthogonal projections," IEEE Transactions on Information Theory, Vol. 44, No. 7, 2943-2959, 1998.
    doi:10.1109/18.737524

    7. Peckham, C. D., et al., "Reduced-rank STAP performance analysis," IEEE Transactions on Aerospace and Electronic Systems, Vol. 36, No. 2, 664-676, 2000.
    doi:10.1109/7.845257

    8. Huang, Q. D., L. R. Zhang, and G. Y. Lu, "Interference suppression method for space-time navigation receivers based on samples selection Householder multistage wiener filter," IEEE International Conference on Signal Processing, 2010.
    doi:10.1109/TSP.2009.2031732

    9. Qiu, S., et al., "A robust reduced-rank monopulse algorithm based on variable-loaded MWF with spatial blocking broadening and automatic rank selection," Digital Signal Processing, Vol. 78, 205-217, 2018.
    doi:10.1016/j.dsp.2018.02.015

    10. He, S., Z. W. Yang, and G. S. Liao, "Adaptive reduced-rank beamforming method based on knowledge-aided joint iterative optimization," IEEE Geoscience and Remote Sensing Letters, Vol. 13, No. 10, 1582-1586, 2016.
    doi:10.1109/LGRS.2016.2600752

    11. Song, N., et al., "Adaptive widely linear reduced-Rank beamforming based on joint iterative optimization," IEEE Signal Processing Letters, Vol. 21, No. 3, 265-269, 2014.
    doi:10.1109/LSP.2013.2295943

    12. Li, D. G., et al., "An improved space-time joint anti-jamming algorithm based on variable step LMS," Tsinghua Science and Technology, Vol. 22, No. 5, 76-84, 2017.
    doi:10.23919/TST.2017.8030541

    13. Zhao, Y., W. X. Li, X. J. Mao, and N. Zhang, "Null broadening beamforming against array calibration errors," Journal of Harbin Engineering University, Vol. 39, No. 1, 163-168, 2018.

    14. Li, W. X., X. J. Mao, and Y. X. Sun, "A new algorithm for null broadening beamforming," Journal of Electronics and Information Technology, Vol. 36, No. 12, 2882-2888, 2014.

    15. Mao, X. J., W. X. Li, and Y. S. Li, "Robust adaptive beamforming against signal steering vector mismatch and jammer motion," International Journal of Antennas and Propagations, Vol. 10, 1-12, 2015.

    16. 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

    17. 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

    18. Zhang, Y. P., Y. J. Li, and M. G. Gao, "Robust adaptive beamforming based on the effectiveness of reconstruction," Signal Processing, Vol. 120, 572-579, 2016.
    doi:10.1016/j.sigpro.2015.09.039

    19. Huang, F., et al., "A fast adaptive reduced rank transformation for minimum variance beamforming," Signal Processing, Vol. 92, No. 12, 2881-2887, 2012.
    doi:10.1016/j.sigpro.2012.05.017

    20. Du, R., F. Liu, K. Tang, and H. Song, "Adaptive antijamming based on space-time 2-D sparse array for GNSS receivers," Progress In Electromagnetics Research M, Vol. 96, 89-97, 2020.
    doi:10.2528/PIERM20070302