AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Tsinghua Science and Technology Article
PDF (4.5 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

An Improved Space-Time Joint Anti-jamming Algorithm Based on Variable Step LMS

College of Information Engineering, Taiyuan University of Technology, Taiyuan 030600, China.
Show Author Information

Abstract

In wireless communication, the space-time anti-jamming method is widely applied because it shows better performance than the pure airspace and pure temporal anti-jamming methods. However, its application is limited by its computational complexity, and it cannot suppress narrowband interference that is in the same direction as the navigation signal. To solve these problems, we propose improved frequency filter to filter the narrowband interference from the desired signal direction in advance, meanwhile, an improved variable step Least Mean Square (LMS) method is proposed to complete the space-time array weights with fast iteration, thereby reducing computational complexity. The simulation results show that, compared with conventional methods, the anti-jamming capability of the proposed algorithm is significantly enhanced; and its complexity is significantly reduced.

Keywords

Space-Time Adaptive Processing (STAP)Least Mean Square (LMS)computational complexityfrequency domain filter

References

[1]
Zhou Z., Wu C., Yang Z., and Liu Y., Sensorless sensing withh WiFi, Tsinghua Science and Technology, vol. 20, no. 1, pp. 1-6, 2015.
Crossref Google Scholar
[2]
Chen Y. H., Juang J. C., Seo J., Lo S., Akos D. M., De Lorenzo D. S., and Enge P., Design and implementation of real-time software radio for anti-interference GPS/WAA sensors, Sensors, vol. 12, no. 10, pp. 13417-13440, 2012.
Crossref Google Scholar
[3]
Motella B., Savasta S., Margaria D., and Dovis F., Method for assessing the interference impact on GNSS receivers, IEEE Trans. Aero. Elec. Sys., vol. 47, no. 2, pp. 1416-1432, 2011.
Crossref Google Scholar
[4]
Xiang C., Feng D., Cao Y., and LV H., Three-dimensional spatial temporal dimension reduced adaptive processing for airborne radar, Systems Engineering and Electronics, vol. 33, no. 3, pp. 548-551 & 580, 2011.
Google Scholar
[5]
Deng Z., Realization method of space time interference suppression for navigation terminal, Radio Engineering, no. 5, pp. 30-33, 2012.
Google Scholar
[6]
Ebrahimi R. and Seydnejad S. R., Elimination of pre-steering delays in space-time broadband beamforming using frequency domain constraints, IEEE Communications Letters, vol. 17, no. 4, pp. 769-772, 2013.
Crossref Google Scholar
[7]
Myrick W., Zoltowski M., and Goldstein S., Anti-jam space-time preprocessor for GPS based on multistage nested Wiener filter, in MILCOM 1999. IEEE Military Communications. Conference Proceedings (Cat. No.99CH36341), 1999.
[8]
Sun X., Huangfu K., Cheng Z., and Chen Q., Joint space-time anti-jammer processing for GPS receiver, Journal of China Institute of Communication, vol. 24, no. 9, pp. 93-102, 2003.
Google Scholar
[9]
Wang R., Zhang J., Ren S., and Li Q., A reducing iteration orthogonal matching pursuit algorithm for compressive sensing, Tsinghua Science and Techology, vol. 21, no. 1, pp. 71-79, 2016.
Crossref Google Scholar
[10]
Zhang H., Yang Y., and Wang X., Research on variable step size LMS adaptive beam-forming algorithm for smart antenna, Computer Simulation, vol. 31, no. 8, pp. 199-203, 2014.
Google Scholar
[11]
Lu B. and Feng C., A new variable STELR size LMS algorithm based on sine function, (in Chinese), Journal of Air Force Engineering University (Natural Science Edition), vol. 14, no. 2, pp. 47-50, 2013.
Crossref Google Scholar
[12]
Wei W. and Zuo T., A modified variable step size LMS adaptive filtering algorithm in satellite communication, (in Chinese), Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), vol. 26, no. 1, pp. 42-48, 2014.
Google Scholar
[13]
Au W., Chen L., Loo K., Pabon A., Xiao Y., and Hwang K., Simulation study of wideband interference rejection using STAP, presented at 2006 IEEE Aerospace Conference, Big Sky, MT, USA, 2006.
[14]
Ren C. and Wang Y. Q., An improved anti-jamming algorithm based on space-time adaptive processing, Acta Armamentarii, vol. 31, no. 12, pp. 1622-1626, 2010.
Google Scholar
[15]
Qiu L., Cai Y., and Zhao M., Low complexity variable forgetting factor mechanisms for adaptive linearly constrained minimum variance beamforming algorithms, IET Signal Process, vol. 9, no. 2, pp. 154-165, 2015.
Crossref Google Scholar
[16]
Cai Y., de Lamare R. C., and Zhao M., Low-complexity variable forgetting factor mechanism for blind adaptive constrained constant modulus algorithms, IEEE Transactions on Signal Processing, vol. 60, no. 8, pp. 3988-4002, 2012.
Crossref Google Scholar
[17]
Phelan J. C., Link B. G., Stueve A., and Pescosolido B. A., Have public conceptions of mental health changed in the past half century? Does it matter? presented at the 124th Annu. Meeting American Public Health Association, New York, NY, USA, 1969.
Tsinghua Science and Technology
Volume 22 Issue 5,
October 2017
Pages 520-528
DOI: 10.23919/TST.2017.8030541
Cite this article:
Li D, Liu J, Zhao J, et al. An Improved Space-Time Joint Anti-jamming Algorithm Based on Variable Step LMS. Tsinghua Science and Technology, 2017, 22(5): 520-528. https://doi.org/10.23919/TST.2017.8030541

765

Views

57

Downloads

5

Crossref

N/A

Web of Science

9

Scopus

1

CSCD

Altmetrics
Received: 25 July 2016
Revised: 17 October 2016
Accepted: 20 October 2016
Published: 11 September 2017
© The author(s) 2017
Return