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Jamming Method Based on Optimal Power Difference for LMS-GPS Receiver
Progress In Electromagnetics Research M, Vol. 77, 167-175, 2019
Jamming and anti-jamming techniques for global position systems (GPS) play important roles in electronic countermeasure. Least mean square (LMS)-based anti-jamming algorithm is widely used in GPS receivers, since it can avoid matrix inversion and has low complexity. For convenience, we call them LMS-GPS receivers. To improve the anti-jamming performance of the LMS-GPS receivers, it is very meaningful to study the jamming technique. Considering that existing jamming signals are easily suppressed by LMS-GPS receivers, a new jamming method named as optimal power difference jamming is proposed in this paper to improve the jamming effect further. Specifically, the analytical relationship between jamming-to-signal ratio (JSR) and the power difference of two interference signals is firstly given. Then, the conclusion that there is always an optimal power difference where the JSR can take the extreme value is drawn. Finally, the optimal power difference is derived as about 22 dB for single-tone interference and 29 dB for band-limited Gaussian noise interference. Simulation results show that the proposed method with optimal power difference is able to improve the JSR remarkably.
Fulai Liu, Yadong Wang, Ling Yue, Xiaodong Kan, and Hui Song, "Jamming Method Based on Optimal Power Difference for LMS-GPS Receiver," Progress In Electromagnetics Research M, Vol. 77, 167-175, 2019.

1. Pinker, A. and C. Smith, "Vulnerability of the GPS Signal to Jamming," GPS Solutions, Vol. 3, No. 2, 19-27, 1999.

2. Kamatham, Y., B. Kinnara, and M. K. Kartan, "Mitigation of GPS multipath using affine combination of two LMS adaptive filters," IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems, Vol. 35, 1-4, 2015.

3. Ahmad, Z., M. Tahir, and I. Ali, "Analysis of beamforming algorithms for antijams," 2013 XVIIIth International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED), 89-96, 2013.

4. Chan, S. C. and Y. Zhou, "Improved generalized-proportionate stepsize LMS algorithms and performance analysis," IEEE International Symposium on Circuits and Systems, 2325-2328, 2006.

5. Gardner, W., "Nonstationary learning characteristics of the LMS algorithm," IEEE Transactions on Circuits and Systems, Vol. 34, No. 10, 1199-1207, 2003.

6. Luo, H., "Accurate analysis of processing gain in direct sequence spread spectrum communication systems under single-tone and narrowband interference," Telecommunication Engineering, 2014.

7. Pazaitis, D. I. and A. G. Constantinides, "A novel kurtosis driven variable step-size adaptive algorithm," IEEE Transactions on Signal Processing, Vol. 47, No. 3, 864-872, 1999.

8. Duttweiler, D. L., "Proportionate normalized least-mean-squares adaptation in echo cancelers," IEEE Transactions on Speech and Audio Processing, Vol. 8, No. 5, 508-518, 2002.

9. Ye, F., H. Tian, and F. Che, "CW interference effects on the performance of GPS receivers," 2017 Progress In Electromagnetics Research Symposium - Fall (PIERS - FALL), 66-72, 2017.

10. Mao, Y. and C. Guo, "Analysis of interference effect on signal acquisition and tracking of GPS receiver," IEEE International Conference on Communication Problem-Solving, 592-595, 2014.

11. Balaei, A. T., A. G. Dempster, and L. L. Presti, "Characterization of the effects of CW and pulse CW interference on the GPS signal quality," IEEE Transactions on Aerospace and Electronic Systems, Vol. 45, No. 4, 1418-1431, 2009.

12. Betz, J. W. and K. R. Kolodziejski, "Generalized theory of code tracking with an early-late discriminator Part II: Noncoherent processing and numerical results," IEEE Transactions on Aerospace and Electronic Systems, Vol. 45, No. 4, 1557-1564, 2009.

13. 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.

14. Turan, C., M. S. Salman, and A. Eleyan, "A new variable step-size block LMS algorithm for a non-stationary sparse systems," International Conference on Electronics Computer and Computation, 1-4, 2016.