Science China Information Sciences

, Volume 53, Issue 8, pp 1653–1665 | Cite as

An approach to forward looking FMCW radar imaging based on two-dimensional Chirp-Z transform

Research Papers


Airborne forward looking radar imaging, which is an important work mode of imaging radar system, has many advantages combined with frequency modulated continuous wave (FMCW) technology. This paper studies the configuration with one central antenna element for signal transmitting and other antenna elements for signal receiving. According to its imaging geometry, the analytical expression of the received signal for forward looking imaging radar based on FMCW is given. By performing the equivalent phase center principle, the received signal is equalized to the case of system configuration with antenna both for transmitting and receiving signals. The Doppler frequency shift effect, induced by the platform’s continuous motion while radar transmits and receives signals, is analyzed in detail and the approximate compensation method is shown. Based on this, a novel method for forward looking FMCW radar imaging is developed, which adopts two-dimensional Chirp-Z transform to implement scaling operation. Also the complete derivation process of the algorithm and the expression of each compensation factor are presented. The whole algorithm only includes FFT and complex multiplication, with interpolation free, and is easy to implement in reality. Simulation results verify the correctness of the analysis and the validity of the proposed algorithm.


forward looking radar imaging FMCW Chirp-Z transform 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Liu Q. Progress and prospect of enhanced vision radar. Modern Radar, 2001, 23(4): 7–10Google Scholar
  2. 2.
    Chen Q, Yang R L. Research of chirp scaling imaging algorithm for air-borne forward-looking SAR. J Electr Inf Tech, 2008, 30(1): 228–232Google Scholar
  3. 3.
    Mittermayer J, Wendler M, Krieger G. Sector imaging radar for enhanced vision (SIREV): Simulation and processing techniques. In: Enhanced and Synthetic Vision 2000, Proceeding of SPIE, Orlando, FL, USA, 2000. 4023: 298–305Google Scholar
  4. 4.
    Krieger G, Mittermayer J, Wendler M. Sector imaging radar for enhanced vision. Aerospace Sci Tech, 2003, 7: 147–158MATHCrossRefGoogle Scholar
  5. 5.
    Liu G Y, Huang S J. The study on the algorithm and imaging of the squint and forward-looking SAR system. Doctoral Dissertation. Cheng du: University of Electronic Science and Technology, 2002Google Scholar
  6. 6.
    Moreira A, Mittermayer J, Scheiber R. Extend chirp scaling algorithm for air- and spaceborne SAR data processing in stripmap and scansar imaging modes. IEEE Trans GRS, 1996, 34(5): 1123–1136Google Scholar
  7. 7.
    Edrich M. Ultra-light weight synthetic aperture radar based on a 35 GHz FMCW sensor concept and online raw data transmission. In: IEE Proc Radar Sonar Navig, 2006, 153(2): 129–134CrossRefGoogle Scholar
  8. 8.
    Meta A, de Wit J J M, Hoogeboom P. Development of high resolution airborne millimeter wave FM-CW SAR. In: Proc EuRAD’04, Amsterdam, Netherlands, 2004. 209-212Google Scholar
  9. 9.
    Sutor T, Buckreuss S, Krieger G. Sector imaging radar for enhanced vision (sirev): theory and applications. In: Enhanced and Synthetic Vision 2000, Proceedings of SPIE, Orlando, FL, USA, 2000. 4023: 292–297Google Scholar
  10. 10.
    Li Z F. Approaches to SAR-InSAR-GMTI for distributed small satellite SAR systems. Doctoral Dissertation. Xi’an: Xidian university, 2006Google Scholar
  11. 11.
    Krieger G, Gebert N, Moreira A. Multidimensional Waveform encoding: a new digital beamforming technique for synthetic aperture radar remote sensing. IEEE Trans GRS, 2008, 46(1): 31–46Google Scholar
  12. 12.
    Bao Z, Xing M D, Wang T. Radar Imaging Technology. Publishing house of electronics industry, 2005, Beijing, China.Google Scholar
  13. 13.
    Meta A, Hoogeboom P. Signal processing algorithms for FMCW moving target indicator synthetic aperture radar. In: Proc IGARSS’05, Seoul, Korea, July 2005. 316–319Google Scholar
  14. 14.
    Jiang Z H, Huangfu K, Wan J W. A chirp transform algorithm for processing squint mode FMCW SAR data. IEEE Geosci Remote Sens Lett, 2007, 4(3): 377–381CrossRefGoogle Scholar
  15. 15.
    de Wit J J M, Meta A, Hoogeboom P. Modified range-doppler processing for FM-CW synthetic aperture radar. IEEE Geosci Remote Sens Lett, 2006, 3(1): 83–87CrossRefGoogle Scholar
  16. 16.
    Mittermayer J, Moreira A, Loffeld O. Spotlight SAR data processing using the frequency scaling algorithm. IEEE Trans Geosci Remote Sens, 1999, 37(5): 2198–2214CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yi Liang
    • 1
  • HongXian Wang
    • 1
  • Long Zhang
    • 1
    • 2
  • Zheng Bao
    • 1
  1. 1.National Key Lab of Radar Signal ProcessingXidian UniversityXi’anChina
  2. 2.Xi’an Polytechnic UniversityXi’anChina

Personalised recommendations