Remote sensing of the Earth by synthetic aperture radar

A.N. Leukhin, V.I. Bezrodnyi, A.A. Voronin*

Mari State University, Yoshkar-Ola, 424000 Russia

E-mail: *v.andrei@protonmail.com

Received November 9, 2017

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Abstract

A synthetic aperture radar is usually a complex software and hardware system. It allows obtaining images in radio range comparable in resolution with optical systems. The advantage of radio waves is that the images are of high quality, despite cloudiness and dark time. The development of algorithms for such systems is a rather complex process. In this case, mathematical modeling i s applied in purpose to reduce costs. In this paper, an overview of the earlier created systems has been provided. We have discussed the methods for calculating the scattered electromagnetic field. We have identified the methods that are most suitable for simulating a synthetic aperture radar. Combination of different approximation methods allows to process large scenes. Various effects that arise upon the propagation of radio waves have been taken into account. We have also described the algorithms for synthesis of radar images. In particular, we have considered the range-migration and time-frequency processing algorithms. We have shown that the frequency-time processing algorithm is preferable for synthesis of radio images in the X-band due to its speed. In opposite, the range-migration effect in P-band is too strong to ignore it. The time-frequency algorithm does not give a focused image with serious artifacts. It is better to use the range-migration algorithm for P-band.

Keywords: synthetic aperture radar, scattering model, radar images, math modeling

Acknowledgments. The study was supported by the Russian Foundation for Basic Research (project no. 15-07-99514) and by the grant of the Ministry of Education and Science of the Russian Federation (projects nos. 2.2226.2017/PCh and 2.9140.2017/BCh).

Figure Captions

Fig. 1. The operating principle of synthetic aperture radars.

Fig. 2. A facet model of radar echo from the Earth's surface (maximum impact in the radar echo is made by the facet that is perpendicular to the radiation): 1 – facet; 2 – local diagram of backward radiation; 3 – surface.

Fig. 3. Counting migration based on distances on the long-wave hologram of "high" resolution.

Fig. 4. An algorithm of distance migration in the P-range.

Fig. 5. An algorithm of time-and-frequency processing in the P-range.

Fig. 6. An algorithm of distance migration in the X-range.

Fig. 7. An algorithm of time-and-frequency processing in the X-range.

References

1. Hwang J.-T., Hong S.-Y., Song J.-H., Kwon H.-W. Radar cross section analysis using physical optics and its applications to marine targets. J. Appl. Math. Phys., 2015, vol. 3, no. 2, pp. 166–171. doi: 10.4236/jamp.2015.32026.

2. Rajyalakshmi P., Raju G.S.N. Characteristics of radar cross section with different objects. Int. J. Electron. Commun. Eng., 2011, vol. 4, no. 2, pp. 205–216.

3. Sasi Bhushana Rao G., Nambari Swathi, Kota Srikanth, Ranga Rao K.S. Monostatic radar cross section estimation of missile shaped object using physical optics method. IOP Conf. Ser.: Mater. Sci. Eng., 2017, vol. 225, art. 012278, pp. 1–7. doi: 10.1088/1757-899X/225/1/012278.

4. Gibson W.C. The Method of Moments in Electromagnetics. Chapman and Hall/CRC, 2007. 288 p.

5. Gallagher R.H. Finite Element Analysis. Fundamentals. Englewood Cliffs, New Jersey, Prentice-Hall, 1975. 416 p.

6. Borzov A.B., Sokolov A.V., Suchkov V.B. Methods for digital modeling of the radar characteristics of complex objects against the background of natural and anthropogenic objects. Zh. Radioelektron., 2000, no. 3. Available at: jre.cplire.ru/jre/mar00/index.html/. (In Russian)

7. Borzov A.B., Sokolov A.V., Suchkov V.B. digital modeling of input signals of the short-range radiolocation systems from complex radar scenes. Zh. Radioelektron., 2004, no. 4. Available at: jre.cplire.ru/jre/apr04/index.html/. (In Russian)

8. Suchkov V.B. The object-oriented method for determining the complex reflection coefficients of the polygonal model of the location object. Sist. Sredstva Svyazi, Telev. Radioveshchaniya, 2013, nos. 1–2, pp. 159–165. (In Russian)

9. Neronskii L.B., Mikhailov V.F., Bragin I.V. Mikrovolnovaya apparatura distantsionnogo zondirovaniya poverkhnosti Zemli i atmosfery: Radiolokatory s sintezirovannoi aperturoi antenny [Microwave Equipment for Earth Surface and Atmosphere Remote Sensing: Synthetic Aperture Radars]. St. Petersburg, S.-Peterb. Gos. Univ. Aerokosm. Priborostr., 1999. 220 p. (In Russian)

10. Chernyi F.B. Rasprostranenie radiovoln [Radio Waves Distribution]. Moscow, Sov. Radio, 1962. 480 p. (In Russian)

11. ITU-R Recommendation R.835-5 Reference Standard Atmospheres.

12. Baskakov A.I., Zhutyaeva T.S., Lukashenko Yu.I. Lokatsionnye metody issledovaniya ob"ektov i sred [Radar Methods for Studying Objects and Media]. Moscow, Akademiya, 2011. 380 p. (In Russian)

13. Zubkovich S.G. Statisticheskie kharakteristiki radiosignalov, otrazhennykh ot zemnoi poverkhnosti [Statistical Characteristics of Radio Signals from the Earth Surface]. Moscow, Sov. Radio, 1968. 223 p. (In Russian)

14. Rozhentsov A.A., Baev A.A., Naumov A.S. Estimation of parameters and recognition of images of three-dimensional objects with disordered samples. Optoelectron. Instrument. Proc., 2010, vol. 46, no. 1, pp. 46–55. doi: 10.3103/S8756699010010061.

15. Shiro E.G. Methods and equipment for digital synthesis of high-quality radar images. Cand. Tech. Sci. Diss. Moscow, 2001. 165 p. (In Russian)

16. Shkol'nyi L.A., Tolstov E.F., Detkov A.N., Tonkikh O.A., Tsvetkov O.A., Arkhangel'skii A.S. Radiolokatsionnye sistemy vozdushnoi razvedki, deshifrovaniya radiolokatsionnykh izobrazhenii [Radar Systems of Aerial Survey, Interpretation of Radar Images]. Moscow, Izd. VVIA im. Prof. N.E. Zhukovskogo, 2008. 531 p. (In Russian)

For citation : Leukhin A.N., Bezrodnyi V.I., Voronin A.A. Remote sensing of the Earth by synthetic aperture radar. Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 2018, vol. 160, no. 1, pp. 25–41. (In Russian)

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