Skip to main content
Log in

Improving Target Detection Ability Based on Time Invariant and Dot-Shape Beamforming in TMRC-FDA-MIMO Radar

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Frequency diverse array and multiple-input multiple-output (FDA-MIMO) radar is studied more to realise the joint estimation of range and angle. However, the estimation performance of target parameters for linear FDA radar with an identical frequency increment and multiple-input multiple-output (IFI-FDA-MIMO) and logarithmically increased frequency offset linear interval, and multiple-input multiple-output (LIFO-FDA-MIMO) is fundamentally limited by the periodic range-time variation and time-variant dot shape beampattern respectively. In this article, we proposed a joint range and angle estimation algorithm based on a new waveform synthesis model of time modulation and rang compensation FDA-MIMO (TMRC-FDA-MIMO). The emulation results demonstrate that the improved scheme achieves the goal of time-invariant, dot-shaped and low sidelobe beampattern, which is optimised by a new accelerated particle swarm optimisation (NAPSO) algorithm. The performance of target estimation under the Cramer Rao lower bound (CRLB), and the root means square errors (RMSE) of the radar system is analysed. Moreover, the mathematical formula derivation and numerical results verify the performance of the proposed algorithm, which shows that TMRC-FDA-MIMO radar system is superior to others mentioned above.

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

Access this article

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

Similar content being viewed by others

References

  1. Wen, F.-Q., & Zhang, G. (2015). Multi-way compressive sensing based 2d doa estimation algorithm for monostatic mimo radar with arbitrary arrays. Wireless Personal Communications, 85(4), 2393–2406.

    Article  Google Scholar 

  2. Bobo Fu, & Hanying Hu. (2016). A two-dimensional DOA estimation algorithm based on propagator for monostatic MIMO radar. International Conference on Wireless Communications. IET.

  3. He, J., Swamy, M. N., & Ahmad, M. O. (2011). Joint DOD and DOA estimation for MIMO array with velocity receive sensors. IEEE Signal Processing Letters, 18, 399–402.

    Article  Google Scholar 

  4. Dong, Z., Yongshun, Z., Guimei, Z., Cunqian, F., & Jun, T. (2017). Esprit-like two-dimensional doa estimation for monostatic mimo radar with electromagnetic vector received sensors under the condition of gain and phase uncertainties and mutual coupling. Sensors. https://doi.org/10.3390/s17112457.

    Article  Google Scholar 

  5. Antonik, P., Wicks, M. C., Griffiths, H. D., & Baker, C. J. (2006). Frequency diverse array radars. Radar, 2006 IEEE Conference on. IEEE.

  6. M.C. Wicks, P. (2008) Antonik, frequency diverse array with independent modulation of frequency, amplitude, and phase, U.S. Patent 7,319,427 B2.

  7. Xu, J., Liao, G., Zhu, S., Huang, L., & So, H. C. (2015). Joint range and angle estimation using mimo radar with frequency diverse array. Signal Processing IEEE Transactions on, 63(13), 3396–3410.

    Article  MathSciNet  Google Scholar 

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

    Google Scholar 

  9. Khan, W., Qureshi, I. M., Basit, A., et al. (2017). MIMO-frequency diverse array radar with unequal subarrays for improved range-angle dependent beamforming. Wireless Personal Communications, 97, 1967–1984. https://doi.org/10.1007/s11277-017-4590-8.

    Article  Google Scholar 

  10. Gao, K., Shao, H., Chen, H., Cai, J., & Wang, W. Q. (2015). Impact of frequency increment errors on frequency diverse array mimo in adaptive beamforming and target localization. Digital Signal Processing, 44, 58–67.

    Article  Google Scholar 

  11. Zhuang, L., & Liu, X. (2009). Application of frequency diversity to suppress grating lobes in coherent mimo radar with separated subapertures. Eurasip Journal on Advances in Signal Processing, 2009(1), 481792.

    Article  Google Scholar 

  12. Shanbhag, K. V., Deb, D., & Kulkarni, M.. (2010). MIMO radar with spatial-frequency diversity for improved detection performance. IEEE International Conference on Communication Control & Computing Technologies. IEEE.

  13. Qin, S., Zhang, Y. D., Amin, M. G., & Gini, F. (2017). Frequency diverse coprime arrays with coprime frequency offsets for multitarget localization. IEEE Journal of Selected Topics in Signal Processing, 11(2), 321–335.

    Article  Google Scholar 

  14. Yao, A. M., Wu, W., & Fang, D. G. (2016). Frequency diverse array antenna using time-modulated optimized frequency offset to obtain time-invariant spatial fine focusing beampattern. IEEE Transactions on Antennas and Propagation, 64(10), 4434–4446.

    Article  MathSciNet  Google Scholar 

  15. Wang, Z., Song, Y., Mu, T., & Ahmad, Z. (2018). A short-range range-angle dependent beampattern synthesis by frequency diverse array. IEEE Access, 6(99), 22664–22669.

    Article  Google Scholar 

  16. Yan, Y., Cai, J., & Wang, W. Q. (2019). Two-stage esprit for unambiguous angle and range estimation in fda-mimo radar. Digital Signal Processing. https://doi.org/10.1016/j.dsp.2019.06.002.

    Article  Google Scholar 

  17. Wang, W. Q. (2014). Subarray-based frequency diverse array radar for target range-angle estimation. Aerospace and Electronic Systems IEEE Transactions on, 50(4), 3057–3067.

    Article  Google Scholar 

  18. Wang, W. Q., & Shao, H. (2014). Range-angle localization of targets by a double-pulse frequency diverse array radar. Selected Topics in Signal Processing, IEEE Journal of, 8(1), 106–114.

    Article  Google Scholar 

  19. Aaron M. Jones, & Brian D. Rigling. (2012). Frequency diverse array radar receiver architectures. International Waveform Diversity & Design Conference.

  20. Jones, A. M., & Rigling, B. D.. (2012). Planar frequency diverse array receiver architecture. IEEE Radar Conference. IEEE.

  21. Jones, A.M. (2011). Frequency diverse array receiver architectures, Master’s thesis, Wright State University.

  22. Fartookzadeh, M., & Armaki, S. H. M. (2018). Synthesis of serial-fed frequency diverse arrays with periodic triangular frequency-modulated continuous waveform. IEEE Antennas and Wireless Propagation Letters, 17(2), 263–266.

    Article  Google Scholar 

  23. Guo, R., Ni, Y., Liu, H., Wang, F., & He, L. (2017). Signal diverse array radar for electronic warfare. IEEE Antennas & Wireless Propagation Letters, 16, 2906–2910.

    Article  Google Scholar 

  24. Wang, W. Q. (2016). Overview of frequency diverse array in radar and navigation applications. Radar, Sonar & Navigation, IET, 10(6), 1001–1012.

    Article  Google Scholar 

  25. Xu, Y., Shi, X., Xu, J., & Li, P. (2015). Range-angle-dependent beamforming of pulsed frequency diverse array. IEEE Transactions on Antennas & Propagation, 63(7), 3262–3267.

    Article  MathSciNet  Google Scholar 

  26. Wang, W. Q., So, H. C., & Farina, A. (2017). An overview on time/frequency modulated array processing. Selected Topics in Signal Processing, IEEE Journal of, 11(2), 228–246.

    Article  Google Scholar 

  27. Wang, Y., Huang, G., & Li, W.. (2016). Transmit beampattern design in range and angel domains for mimo frequency diverse array radar. IEEE Antennas and Wireless Propagation Letters, 1–1.

  28. Gui, R., Wang, W. Q., Cui, C., & So, H. C. (2018). Coherent pulsed-fda radar receiver design with time-variance consideration: sinr and crb analysis. IEEE Transactions on Signal Processing, 66(1), 200–214.

    Article  MathSciNet  Google Scholar 

  29. Yang, K., Hong, S., Zhu, Q., & Ye, Y. (2020). Maximum likelihood angle-range estimation for monostatic fda-mimo radar with extended range ambiguity using subarrays. International Journal of Antennas and Propagation, 2020, 1–10.

    Google Scholar 

  30. Wang, C., Zheng, W., Gong, P., & Li, Z. (2020). Joint angle and range estimation in the fda-mimo radar: the reduced-dimension root music algorithm. Wireless Personal Communications. https://doi.org/10.1007/s11277-020-07694-4.

    Article  Google Scholar 

  31. Chu, W., Liu, Y., Li, X., et al. (2020). Optimization of emission waveform by accelerated particle swarm algorithm based on logarithmic frequency offset mathematical model. Wireless PersCommun. https://doi.org/10.1007/s11277-020-07184-7.

    Article  Google Scholar 

  32. Khan, W., Qureshi, I. M., Basit, A., & Khan, W. (2015). Range-bins-based mimo frequency diverse array radar with logarithmic frequency offset. IEEE Antennas and Wireless Propagation Letters, 15, 885–888.

    Article  Google Scholar 

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

    Google Scholar 

  34. Wang, & W.-Q. . (2013). Range-angle dependent transmit beampattern synthesis for linear frequency diverse arrays. IEEE Transactions on Antennas and Propagation, 61(8), 4073–4081.

    Article  MathSciNet  Google Scholar 

  35. Da-Gang Fang, A-Min Yao, & Wen Wu. (2016). Synthesis of 4-D beampatterns using 4-D arrays. IEEE International Symposium on Antennas & Propagation. IEEE, 703–704.

  36. Wang, C., Li, Z., & Zhang, X. (2020). Fda-mimo for joint angle and range estimation: unfolded coprime framework and parameter estimation algorithm. IET Radar, Sonar & Navigation, 14(6), 917–926.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yunqing Liu.

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

Chu, W., Liu, Y., Li, X. et al. Improving Target Detection Ability Based on Time Invariant and Dot-Shape Beamforming in TMRC-FDA-MIMO Radar. Wireless Pers Commun 119, 845–863 (2021). https://doi.org/10.1007/s11277-021-08240-6

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-021-08240-6

Keywords

Navigation