A Novel Method for GPS Anti-jamming Based on Blind Source Separation

The weakness of Global Positioning System (GPS) is easy to be jammed, so the study of GPS anti-jamming of has drawn widely attention. The space-domain GPS anti-jamming based on antennas can effectively suppress the interference, however, when GPS and jamming signals come from the same direction, the traditional anti-jamming ability decline sharply. A novel anti-jamming method based on BSS is proposed in this paper to solve this problem. In this paper, Wavelet De-noising is used to eliminate the effect of noise on signals, and BSS is applied to separate GPS from jamming signals. According to separation principle, the cost function is constructed, Newton iterative algorithm is utilized to gain separated signals which contain GPS. Simulation results show that our method is practically feasible for GPS anti-jamming.

[1]  Gaoming Huang,et al.  A radar anti-jamming technology based on blind source separation , 2004, Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004..

[2]  Dr. Adam Filios.  TELECOMMUNICATIONS TECHNOLOGY , 2001 .

[3]  Lin Li,et al.  Research on GPS anti-jamming algorithm based on adaptive antennas , 2010, 2010 International Symposium on Signals, Systems and Electronics.

[4]  Christian Jutten,et al.  Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..

[5]  Hui Hu,et al.  A study of GPS jamming and anti-jamming , 2009, 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS).

[6]  Huang Gao-ming.  A radar anti-jamming technology based on blind source separation , 2004 .

[7]  Bang-ning Zhang,et al.  Blind source separation in noisy environment and applications in satellite communication anti-jamming , 2009, 2009 Asia-Pacific Conference on Computational Intelligence and Industrial Applications (PACIIA).

[8]  Xu Huang.  An improved FastICA algorithm for blind signal separation and its application , 2012, 2012 International Conference on Image Analysis and Signal Processing.

[9]  Christian Jutten,et al.  Wavelet denoising for highly noisy source separation , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[10]  Peng Tianliang,et al.  FastICA-EMD algorithm for analysis of the mixed signals in noise , 2011, 2011 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC).