High Resolution MIMO-HFSWR Radar Using Sparse Frequency Waveforms
Guohua WANG, Yilong LU
DOI: 10.4236/wsn.2009.13021   PDF   HTML     7,820 Downloads   13,248 Views   Citations


In high frequency surface wave radar (HFSWR) applications, range and azimuth resolutions are usually lim-ited by the bandwidth of waveforms and the physical dimension of the radar aperture, respectively. In this paper, we propose a concept of multiple-input multiple-output (MIMO) HFSWR system with widely sepa-rated antennas transmitting and receiving sparse frequency waveforms. The proposed system can overcome the conventional limitation on resolutions and obtain high resolution capability through this new configura-tion. Ambiguity function (AF) is derived in detail to evaluate the basic resolution performance of this pro-posed system. The advantages of the system of fine resolution and low peak sidelobe level (PSL) are demon-strated by the AF analysis through numerical simulations. The impacts of Doppler effect and the geometry configuration are also studied.

Share and Cite:

G. WANG and Y. LU, "High Resolution MIMO-HFSWR Radar Using Sparse Frequency Waveforms," Wireless Sensor Network, Vol. 1 No. 3, 2009, pp. 152-162. doi: 10.4236/wsn.2009.13021.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] H. W. H. Leong and B. Dawe, “Channel availability for east coast high frequency surface wave radar systems,” Defence R&D Canada, Technical Report, DREO TR 2001-104, No-vember 2001.
[2] R. J. Riddolls, “A Canadian perspective on high frequency over-the-horizon radar,” Defence R&D Canada, Technical Report, DREO TR 2006-285, December 2006.
[3] D. W. Bliss and K. W. Forsythe, “Multiple-input multi-ple-output (MIMO) radar and imaging: Degrees of freedom and resolution,” Proceedings of the 37th Asilomar Conference on Signal, Systems and Computers, pp. 54–59, November 2003.
[4] J. Li, “MIMO radar: Diversity means superiority,” Proceedings of the 14th Annual Adaptive Sensor Array Processing Work-shop-2006, June 6–7, 2006.
[5] S. Peter, J. Li, and Y. Xie, “On probing single design for MIMO radar,” IEEE Transactions on Signal Processing, Vol. 55, No. 8, pp. 4151–4161, August 2007.
[6] G. San Antonio, D. R. Fuhrmann, and F. C. Robey, “MIMO radar ambiguity function,” in IEEE Journal of Selected Topics in Signal Processing, Vol. 1, No. 1, pp. 167–177, June 2007.
[7] E. Fisher, A. Haimovich, R. Blum, L. Cimini, D. Chizhik, and R. Valenzuela, “Spatial diversity in radars—models and detec-tion performance,” IEEE Transactions on Signal Processing, Vol. 20, No. 3, pp. 823–838, March 2006.
[8] N. H. Lehmann, A. M. Haimovich, R. S. Blum, and L. Cimini, “High resolution capabilities of MIMO radar,” Proceedings of the 40th Asilomar Conference on Signal, Systems and Com-puters, pp. 25–30, November 2006.
[9] D. R. Kirk,J. S. Bergin, P. M. Techau, and J. E. Don Carlos, “Multi-static coherent sparse aperture approach to precision target detection and estimation,” Proceedings of 2005 IEEE Radar Conference, pp. 579–584, May 2005.
[10] G. H. Wang, W. X. Liu, and Y. L. Lu, “Sparse frequency transmit waveform design with soft power constraint by using PSO algorithm,” Proceedings of 2008 IEEE Radar Conference, pp. 1–6, May 2008.
[11] W. X. Liu, Y. L. Lu, and M. Leisturgie, “Optimal sparse waveform design for HFSWR system,” Proceedings of 2007 International Waveform Diversity and Design Conference, pp. 127–130, May 2007.
[12] N. Levanon and E. Mosezen, Radar Signals, John Wiely & Sons, New Jersy, 2004.
[13] B. D. Steinberg and E. H. Attia, “Sidelobe reduction of random arrays by element position and frequency diversity,” IEEE Transactions on Signal Processing, Vol. 31, No. 6, pp. 922–930, November 1983.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.