Skip to main content

Wideband MIMO Radar Waveform Optimization Based on Dynamic Adjustment of Signal Bandwidth

  • Conference paper
  • First Online:
Machine Learning and Intelligent Communications (MLICOM 2017)

Abstract

Considering the need of multi-target imaging, a method about MIMO radar waveform optimization based on dynamic adjustment of signal bandwidth is proposed. At first, the closed-loop feedback between the range profile and the signal bandwidth is established, which can design the required bandwidth of transmit signal in different directions, according to the range profile of targets. And then, considering the request of beampattern and the bandwidth limitation, a waveform optimization model is established and solved. Therefore, the multi-target observation and the dynamic adjustment of the signal bandwidth are accomplished. What’s more, satisfactory imaging results are obtained under the least resource consumption. In the end, the simulation has proved the performance of the algorithm in low SNR circumstance.

Y. Gong—This work was supported by the National Natural Science Foundation of China under Grant 61631019.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Fisher, E., Haimovich, A., Blum, R.S.: MIMO radar: an idea whose time has come. In: Proceedings of IEEE Radar 2004 Conference, PA, pp. 71–78 (2004)

    Google Scholar 

  2. Guang, H., Abeysekera, S.S.: Receiver design for range and doppler sidelobe suppression using MIMO and phased-array radar. IEEE Trans. Sig. Process. 61(6), 1315–1326 (2013)

    Article  MathSciNet  Google Scholar 

  3. Wang, H.J., Xu, H.B., Lu, M.: Technology and application analysis of MIMO radar. J. Radar Sci. Technol. 7(4), 245–249 (2009). (in Chinese)

    Google Scholar 

  4. Haimovich, A., Blum, R.S., Cimini, L.J.: MIMO radar with widely separated antennas. IEEE Sig. Process. Mag. 25(1), 116–129 (2008)

    Article  Google Scholar 

  5. Li, J., Stoica, P.: MIMO radar with colocated antennas. IEEE Sig. Process. Mag. 24(5), 106–114 (2007)

    Article  Google Scholar 

  6. Stoica, P., Li, J., Xie, Y.: On probing signal design for MIMO radar. IEEE Trans. Sig. Process. 55(8), 4151–4161 (2007)

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  8. Li, X., Fan, M.M., Lu, M.: Research advance on cognitive radar and its key technology. J. Acta Electronica Sinica 40(9), 1863–1870 (2012). (in Chinese)

    Google Scholar 

  9. Jiang, T., Wang, S.L.: Research on the system concept and architecture of cognitive radar. J. Aerospace Electron. Warfare 30(2), 30–32 (2014). (in Chinese)

    Google Scholar 

  10. Wang, S.L., He, Q., He, Z.: LFM-based waveform design for cognitive MIMO radar with constrained bandwidth. EURASIP J. Adv. Sig. Process. 89(1), 1–9 (2014)

    Google Scholar 

  11. Shi, J.N., Jiu, B., Liu, H.W., Wang, S.L.: A beampattern design method for airborne MIMO radar based on prior information. J. Electron. Inf. Technol. 57(9), 3533–3544 (2009). (in Chinese)

    Google Scholar 

  12. Chen, C.Y., Vaidyanathan, P.P.: MIMO radar waveform optimization with prior information of the extended target and clutter. IEEE Trans. Sig. Process. 57(9), 3533–3544 (2009)

    Article  MathSciNet  Google Scholar 

  13. Cui, G., Li, H., Rangaswamy, M.: MIMO radar waveform design with constant modulus and similarity constraints. IEEE Trans. Sig. Process. 62(2), 343–353 (2014)

    Article  MathSciNet  Google Scholar 

  14. Leshem, A.: Information theoretic adaptive radar waveform design for multiple extended targets. IEEE J. Sel. Topic 1(1), 42–55 (2007)

    Article  Google Scholar 

  15. Yang, Y., Blum, R.S.: Radar waveform design using minimum mean-square error and mutual information. IEEE Workshop Sens. Array Multichannel Process. 2(4), 234–238 (2006)

    Google Scholar 

  16. Yang, Y., Blum, R.S.: Minimax robust MIMO radar waveform design. IEEE J. Sel. Topic 1(1), 147–155 (2007)

    Article  Google Scholar 

  17. Tang, B., Tang, J., Peng, Y.: MIMO radar waveform design in colored noise based on information theory. IEEE Trans. Sig. Process. 58(9), 4684–4697 (2010)

    Article  MathSciNet  Google Scholar 

  18. He, H., Petre, S., Li, J.: Wideband MIMO systems: signal design for transmit neampattern synthesis. IEEE Trans. Sig. Process. 59(2), 618–628 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi-shuai Gong .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Gong, Ys., Zhang, Q., Li, Km., Chen, Yj. (2018). Wideband MIMO Radar Waveform Optimization Based on Dynamic Adjustment of Signal Bandwidth. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73447-7_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73446-0

  • Online ISBN: 978-3-319-73447-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics