Skip to main content
SpringerLink
Log in

Lagrange Programming Neural Network Approach for Frequency Diverse Array Beampattern Synthesis

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

Different from traditional phased array radar, frequency diverse array (FDA) radar uses a small frequency increment across the array elements; thus, the beampattern of FDA can be performed in both range and angle domains. Nevertheless, the transmit beampattern of conventional FDA is coupled in range and angle domains, which is not suitable for target detection. In this paper, we propose a multi-carrier FDA framework to generate the range-angle-decoupled beampattern. To focus the transmit energy at the desired position and suppress the interference at the undesired position, we then propose a beampattern synthesis approach based on Lagrange programming neural network, which can be implemented by hardware easily. Numerical simulation results demonstrate the effectiveness of the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. P. Antonik, M.C. Wicks, H.D. Griffiths, C.J.Baker, Frequency diverse array radars, in Proceedings of the IEEE Radar Conference, Verona, NY 2006, pp. 215–217. IEEE

  2. S. Arik, An analysis of global asymptotic stability of delayed cellular neural networks. IEEE Trans. Neural Netw. 13(5), 1239–1242 (2002)

    Article  Google Scholar 

  3. A. Basit, W. Khan, S. Khan, I.M. Qureshi, Development of frequency diverse array radar technology: a review. IET Radar Sonar Navig. 12(2), 165–175 (2018)

    Article  Google Scholar 

  4. A. Basit, I.M. Qureshi, W. Khan, A.N. Malik, Range–angle-dependent beamforming for cognitive antenna array radar with frequency diversity. Cogn. Comput. 8(2), 1–13 (2015)

    Google Scholar 

  5. N.M. Botros, M. Abdul-Aziz, Hardware implementation of an artificial neural network using field programmable gate arrays (FPGA’s). IEEE Trans. Ind. Electron. 41(6), 665–667 (2002)

    Article  Google Scholar 

  6. V. Boyd, Faybusovich: convex optimization. IEEE Trans. Autom. Control 51(11), 1859 (2006)

    Article  Google Scholar 

  7. J. Cao, J. Wang, Global asymptotic stability of a general class of recurrent neural networks with time-varying delays. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 50(1), 34–44 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  8. S.L. Chi, J. Sum, H.C. So, A.G. Constantinides, F.K.W. Chan, Lagrange programming neural networks for time-of-arrival-based source localization. Neural Comput. Appl. 24(1), 109–116 (2014)

    Article  Google Scholar 

  9. K. Gao, W.Q. Wang, J. Cai, J. Xiong, Decoupled frequency diverse array range–angle-dependent beampattern synthesis using non-linearly increasing frequency offsets. IET Microw. Antennas Propag. 10(8), 880–884 (2016)

    Article  Google Scholar 

  10. K. Gao, W.Q. Wang, H. Chen, J. Cai, Transmit beamspace design for multi-carrier frequency diverse array sensor. IEEE Sens. J. 16(14), 5709–5714 (2016)

    Article  Google Scholar 

  11. P. Gong, Z. Shao, G. Tu, C. Qin, Transmit beampattern design based on convex optimization for MIMO radar systems. Signal Process. 94(1), 195–201 (2014)

    Article  Google Scholar 

  12. S. Haykin, Cognitive radar: a way of the future. IEEE Signal Process. Mag. 23(1), 30–40 (2006)

    Article  Google Scholar 

  13. W. Khan, I.M. Qureshi, A. Basit, M. Zubair, A double pulse MIMO frequency diverse array radar for improved range-angle localization of target. Wirel. Pers. Commun. 82(4), 1–15 (2015)

    Article  Google Scholar 

  14. W. Khan, I.M. Qureshi, S. Saeed, Frequency diverse array radar with logarithmically increasing frequency offset. IEEE Antennas Wirel. Propag. Lett. 14(1), 499–502 (2015)

    Article  Google Scholar 

  15. F. Li, Delayed Lagrangian neural networks for solving convex programming problems. Neurocomputing 73(10), 2266–2273 (2010)

    Article  Google Scholar 

  16. H. Liu, L. Dong, Z. Yi, T.K. Truong, Simultaneous radio frequency and wideband interference suppression in SAR signals via sparsity exploitation in time-frequency domain. IEEE Trans. Geosci. Remote Sens. PP(99), 1–14 (2018)

    Google Scholar 

  17. R.J. Mailloux, Phased Array Antenna Handbook. Artech House Antennas and Propagation Library, 2nd edn. (Artech House, Boston, 2005)

    Google Scholar 

  18. L. Qingshan, C. Jinde, X. Youshen, A delayed neural network for solving linear projection equations and its analysis. IEEE Trans. Neural Netw. 16(4), 834–843 (2005)

    Article  Google Scholar 

  19. P.F. Sammartino, C.J. Baker, Developments in the frequency diverse bistatic system, in Radar Conference 2009, pp. 1–5

  20. M. Secmen, S. Demir, A. Hizal, T. Eker, Frequency diverse array antenna with periodic time modulated pattern in range and angle, in IEEE Radar Conference 2007, pp. 427–430

  21. H.Z. Shao, J. Dai, J. Xiong, H. Chen, W.Q. Wang, Dot-shaped range-angle beampattern synthesis for frequency diverse array. IEEE Antennas Wirel. Propag. Lett. 15, 1703–1706 (2016)

    Article  Google Scholar 

  22. W.Q. Wang, Cognitive frequency diverse array radar with situational awareness. IET Radar Sonar Navig. 10(2), 359–369 (2016)

    Article  Google Scholar 

  23. J. Xu, S. Zhu, G. Liao, Range ambiguous clutters suppression for airborne FDA-STAP radar. IEEE J. STSP 9(8), 1620–1631 (2015)

    Google Scholar 

  24. Y. Xu, X. Shi, J. Xu, L. Huang, W. Li, Range–angle-decoupled beampattern synthesis with subarray-based frequency diverse array ☆. Digit Signal Process. 64, 49–59 (2017)

    Article  MathSciNet  Google Scholar 

  25. S. Zhang, A.G. Constantinides, Lagrange programming neural networks. IEEE Trans. Circuits Syst. II Analog Digit. Signal Process. 39(7), 441–452 (1992)

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Nanjing Research Institute of Electronic Technology, Nanjing, 210039, China

    Tianfang Chen

  2. National Laboratory of Radar Signal Processing, Xidian University, Xi’an, 710071, China

    Deping Xia

Authors
  1. Tianfang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Deping Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tianfang Chen.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, T., Xia, D. Lagrange Programming Neural Network Approach for Frequency Diverse Array Beampattern Synthesis. Circuits Syst Signal Process 39, 439–455 (2020). https://doi.org/10.1007/s00034-019-01193-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-019-01193-z

Keywords

Search

Navigation