350 rub
Journal Achievements of Modern Radioelectronics №12 for 2022 г.
Article in number:
Algorithm of range migration compensation via the keystone transform without interpolation
Type of article: scientific article
DOI: https://doi.org/10.18127/j20700784-202212-07
UDC: 621.396.96
Authors:

A.A. Monakov1

1 St. Petersburg State University of Aerospace Instrumentation (St. Petersburg, Russia)

Abstract:

Range cell migration is one of the main reasons of deterioration of radar images in radars with synthesized antenna aperture (SAR). Nowadays there are two groups of signal processing algorithms for SAR, which permit to compensate the range cell migrations. The first group includes algorithms that use the recalculation of the signal from the coordinate system "slant range – azimuth" into the system "along‑track range – cross‑track range" using different mathematical methods of functional interpolation. Since the conversion from one coordinate system to another is a fairly costly process, the algorithms of the first group require a significant amount of computing power in implementation, which is a serious drawback of the algorithms of this group. Algorithms of the second group do not use interpolation and are based on transformation of the range cell migrations into the corresponding phase shifts with their further compensation. These algorithms are not inferior in quality to the interpolation methods, but they are also much faster due to the application of fast procedures of the Fourier analysis in calculations. Unfortunately, these methods are difficult to be realized in onboard signal processors because the number of calculations is also large.

The article synthesizes a range migration compensation algorithm that does not use interpolation methods. The synthesized algorithm is a modification of the well-known Keystone Transform Algorithm (KTA). The proposed algorithm is based on the Chirp Scaling Algorithm and the fast procedures of the Fourier spectral analysis. Implementation of the chirp scaling permits to avoid the interpolation in the KTA. Besides the number of complex multiplications is reduced in the proposed algorithm. Thus, the proposed algorithm has a high computational speed and can be used for any sounding wideband signal. Computer simulation proves the high efficiency of the algorithm. The algorithm can be implemented in side looking SAR to synthesize radar images of high spatial resolution.

Pages: 46-54
For citation

Monakov A.A. Algorithm of range migration compensation via the keystone transform without interpolation. Achievements of Modern Radioelectronics. 2022. V. 76. № 12. P. 46–54. DOI: https://doi.org/ 10.18127/j20700784-202212-07 [in Russian]

References
  1. Verba V.S., Neronskij L.B., Osipov I.G., Turuk V.E. Radiolokacionnye sistemy zemleobzora kosmicheskogo bazirovaniya. Pod red.
    V.S. Verby. M.: Radiotekhnika. 2010. 681 s. [in Russian].
  2. Cumming I.G., Bennett J.R. Digital processing of SEASAT SAR data. Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. Washington. DC. USA. Apr. 1979. P. 45–47.
  3. Lin M.Y., Wu C. A SAR correlation algorithm which accommodates large range migration. IEEE Trans. Geosci. Remote Sensing. 1984. V. 22. Nov. № 6. P. 592–597.
  4. Chang C.Y., Jin M., Curlander J.C. Squint mode processing algorithms. Proc. IGARSS, Vancouver. Canada. July 1989. P. 1702–1706.
  5. Smith A. M. A new approach to range-Doppler SAR processing. Int. J. Remote Sensing. 1991. V. 12. Feb. № 2. P. 235–251.
  6. Franceschetti G., Schirinzi G. A SAR processor based on two‑dimensional FFT codes. IEEE Trans. Aerospace Electron. Syst. 1990. V. 26. Mar. № 2. P. 356–366.
  7. Cafforio C., Prati C., Rocca F. SAR data focusing using seismic migration techniques. IEEE Trans. Aerospace Electron. Syst. 1991. V. 27. Mar. № 2. P. 194–207.
  8. Franceschetti G., Lanari R., Marzouk E.S. Aberration free SAR raw data processing via transformed grid predeformation. Proc. IGARSS. Tokyo, Japan. Aug. 1993. P. 1593–1595.
  9. Stolt R.H. Migration by Fourier transform. Geophysics. 1978. V. 43. Jan. № 1. P. 23–48.
  10. Perry R.P., DiPietro R.C., Fante R.L. Coherent Integration with Range Migration Using Keystone Formatting. 2007 IEEE Radar Conference, Boston. MA. USA. April 2007. P. 863–868.
  11. Jing L., Hong G., Weimin S., Mojun Z. A Fast Range Migration Compensation Method. 2nd International Conference on Signal Processing Systems (ICSPS). Dalian. China. July 2010. P. V2-139-V2-143.
  12. Runge H., Bamler R. A novel high precision SAR focusing algorithm based on chirp scaling. Proc. IGARSS. Houston. TX. May 1992. P. 372–375.
  13. Cumming I.G., Wong F., Raney K. A SAR processing algorithm with no interpolation. Proc. IGARSS. Tokyo. Japan. Aug. 1993. P. 376–379.
  14. Wong F., Cumming I.G., Raney R.K. Processing simulated RADARSAT SAR data with squint by a high precision algorithm. Proc. IGARSS. Tokyo. Japan. Aug. 1993. P. 1176–1178.
  15. Raney R.K., Runge H., Bamler R., Cumming I.G., Wong F. Precision SAR processing without interpolation for range cell migration correction. IEEE Trans. Geosci. Remote Sensing. 1994. V. 32. July. No 4. P. 786–799.
  16. Monakov A.A. Algoritm kompensacii migracij svetyashchihsya tochek po dal'nosti v RSA bokovogo obzora. Elektromagnitnye volny i elektronnye sistemy. 2018. T. 23. № 7. S. 6–12 [in Russian].
  17. Moreira A., Huang Y. Airbome SAR Processing of Highly Squinted Data Using a Chirp Scaling Approach with Integrated Motion Compensation. IEEE Trans. Geosci. Remote Sensing. 1994. V. 32. Sept. № 5. P. 1029–1040.
  18. Moreira A., Mittermayer J., Scheiber R. Extended Chirp Scaling Algorithm for Air- and Spaceborne SAR Data Processing in Stripmap and ScanSAR Imaging Modes. IEEE Trans. Geosci. Remote Sensing. 1996. V. 34. Sept. № 5. P. 1123–1136.
  19. Mittermayer J., Moreira A., Loffeld O. Spotlight SAR data processing using the frequency scaling algorithm. IEEE Trans. Geosci. Remote Sensing. 1999. V. 37. Sept. № 5. P. 2198–2214.
  20. Zhu D., Shen M., Zhu Z. Some Aspects of Improving the Frequency Scaling Algorithm for Dechirped SAR Data Processing. IEEE Trans. Geosci. Remote Sensing. 2008. V. 46. June. № 6. P. 1579–1588.
  21. Zhu D., Li Y., Zhu Z. A Keystone Transform without Interpolation for SAR Ground Moving Target Imaging. IEEE Geosci. and Remote Sensing Lett. 2007. V. 4. № 1. P. 18–22.
  22. Monakov A.A., Povarenkin N.V. Ocenka ugla mesta nizkoletyashchej celi: matematicheskaya model' signala, rasseyannogo sheroho-vatoj poverhnost'yu pri skol'zyashchih uglah rasprostraneniya. Uspekhi sovremennoj radioelektroniki. 2019. T. 73. № 11. S. 12–19 [in Russian].
Date of receipt: 6.10.2022
Approved after review: 11.10.2022
Accepted for publication: 21.11.2022