Vol. 43
Latest Volume
All Volumes
2012-09-11
The Verification of Chaotic Characteristics of Radar Angular Glint
By
Progress In Electromagnetics Research B, Vol. 43, 295-311, 2012
Abstract
In this paper, we present the chaotic verification for angular glint of complex radar target. Angular glint is a key factor in the generation loss probability in radar detections, and the intrinsic physical characteristic and suppression techniques of glint have been a hot topic in radar signal analysis. In this paper, the radar angular glint samples of a typical complex target are calculated by the Greco method based on Phase Gradient method. The simulated glint series fit the prerequisites of chaos for deterministic, nonlinear generation and no regularities in time domain, therefore the analysis the chaotic traits is required. We propose the design of chaotic verification flow, which is proved to be efficient and effective by the experiment of Lorenz Attractor signal model, and the details have been explained. The algorithm flow begins with the determination of optimum time lag and minimum embedding dimension, and is followed by the time-delay reconstruction in phase space. The results are presented with three qualitative verification results of attractor geometry, Poincare section and principal component analysis and two quantitative results of correlation dimension and largest Lyapunov exponent for the glint series. With comparison with results obtained by Lorenz attractor, the chaotic traits of angular glint data are verified. Therefore, the paper has proposed new possible reduction and prediction ideas to refrain angular glint in the digital processing unit of radar receiver in the future.
Citation
Jin Zhang, and Jungang Miao, "The Verification of Chaotic Characteristics of Radar Angular Glint," Progress In Electromagnetics Research B, Vol. 43, 295-311, 2012.
doi:10.2528/PIERB12062601
References

1. Howard, D. D., "Radar target glint in tracking and guidance system based on echo signal phase distortion," Proc. of NEC, 840-849, May 1959.

2. Lindsay, J. E., "Angular glint and the moving, rotating, complex radar target," IEEE Trans. on Aerospace and Electronics Systems, Vol. 4, 164-173, Mar. 1968.
doi:10.1109/TAES.1968.5408954

3. Dunn, J. H. and D. D. Howard, "Radar target amplitude angle and Doppler scintillation from analysis of the echo signal propagating in space," IEEE Trans. on Microwave Theory and Techniques, Vol. 16, No. 9, 715-728, Sep. 1968.
doi:10.1109/TMTT.1968.1126776

4. Sinm, R. J. and E. R. Graf, "The reduction of radar glint by diversity techniques," IEEE Trans. on Antenna and Propagation, Vol. 19, No. 4, 462-468, 1971.
doi:10.1109/TAP.1971.1139956

5. Ostrovityanov, R. V. and F. A. Basalov, Statistical Theory of Extended Radar Targets, Ch. 1-Ch. 3, Translated from Russian (Barton. W. F, Barton. D. K), Artech House, MA, 1985.

6. Stadhu, G. S. and A. V. Saylor, "A real-time statistical radar target model," IEEE Trans. on Aerospace and Electronics Systems, Vol. 21, No. 4, 490-507, 1985.
doi:10.1109/TAES.1985.310637

7. Yin, H. C., S. Deng, Y. Ruan, et al. "On the derivation of angular glint from backscattering measurements of each relative phase," Acta Electronica Sinica, Vol. 9, 36-40, 1996 (in Chinese).

8. Yin, H. C. and P. K. Huang, "Unification and comparison between two concepts of radar target angular glint," IEEE Trans. on Aerospace and Electronics Systems, Vol. 31, No. 2, 778-783, 1995.
doi:10.1109/7.381924

9. Juan, M. R., M. Ferrando, and L. Jofre, "GRECO: Graphical electromagnetics computing for RCS prediction in real time," IEEE Antennas and Propagation Magazine, Vol. 35, No. 2, Apr. 1993.

10. Qin, D., "All-band electromagnetic scattering computation for complex targets: Method studies and application software,", Ph.D. Dissertation, Department of Electrical Engineering, Beijing University of Aerosnautics and Astronatics, Beijing, P. R. China, 2004 (in Chinese).

11. Ning, H., N. Fang, and B. Wang, "Visual computing method of radar glint for complex target," Chinese Journal of Electronics, Vol. 15, No. 2, 356-358, 2006 (in Chinese).

12. Kazimierski, W., "Statistical analysis of simulated radar target's movement for the needs of multiple model tracking filter," International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 5, No. 3, Sep. 2011.

13. Li, X. R. and V. P. Jilkov, "A survey of maneuvering target tracking --- Part V: Multiple-model method," IEEE Transactions on Aerospace and Electronic Systems, Vol. 41, 2005.

14. Wolf, A. and T. Bessior, "Diagnosing chaos in the space circle," Physica D: Nonlinear Phenomena, Vol. 50, No. 2, 239-258, 1991.
doi:10.1016/0167-2789(91)90178-C

15. Meiss, J. D. and http://amath.colorado.edu/pub/dynamics/papers/sci.nonlinear-FAQ.pdf., "Asked questions about nonlinear science,".
doi:10.1016/0167-2789(91)90178-C

16. Cao, L., "Practical method for determining the minimum embedding dimension of a scalar time series," Physica D: Nonlinear Phenomena, Vol. 110, No. 1-2, 43-50, 1997.
doi:10.1016/S0167-2789(97)00118-8

17. Campbell, D. K., "Nonlinear science from paradigms and practicalities," Phys. Rec. Lett., Vol. 15, 218-262, 1987.

19. Lv, J. and J. Lu, Chaotic Time Seires: Analysis and Applications, 52-241, Wuhan University Press, Wuhan, 2002 (in Chinese).

20. Merkwirth, C., U. Parlitz, and et al, TSTOOL User Manual, http://www.dpi.physik.uni-goettingen.de/tstool/manual.pdf..

21. Wolf, A., J. B. Swift, L. Swinney, et al. "Determining Lyapunov exponents from a time series," Physica D: Nonlinear Phenomena, Vol. 16, No. 3, 285-317, 1985.
doi:10.1016/0167-2789(85)90011-9