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Adaptive Local Polynomial Fourier Transform in ISAR

Abstract

The adaptive local polynomial Fourier transform is employed for improvement of the ISAR images in complex reflector geometry cases, as well as in cases of fast maneuvering targets. It has been shown that this simple technique can produce significantly improved results with a relatively modest calculation burden. Two forms of the adaptive LPFT are proposed. Adaptive parameter in the first form is calculated for each radar chirp. Additional refinement is performed by using information from the adjacent chirps. The second technique is based on determination of the adaptive parameter for different parts of the radar image. Numerical analysis demonstrates accuracy of the proposed techniques.

References

  1. Wang Y, Ling H, Chen VC: ISAR motion compensation via adaptive joint time-frequency technique. IEEE Transactions on Aerospace and Electronic Systems 1998, 34(2):670–677. 10.1109/7.670350

    Article  Google Scholar 

  2. Barbarossa S, Scaglione A, Giannakis GB: Product high-order ambiguity function for multicomponent polynomial-phase signal modeling. IEEE Transactions on Signal Processing 1998, 46(3):691–708. 10.1109/78.661336

    Article  Google Scholar 

  3. Quinquis A, Ioana C, Radoi E: Polynomial phase signal modeling using warping-based order reduction. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '04), May 2004, Montreal, Quebec, Canada 2: 741–744.

    Google Scholar 

  4. Wong SK, Riseborough E, Duff G: Experimental investigations on the distortion of ISAR images using different radar waveforms. In Tech. Mem. DRDC Ottawa TM 2003-1996. Defence Research & Development Canada, Ottawa, Ontario, Canada; 2003.

    Google Scholar 

  5. Wong SK, Duff G, Riseborough E: Distortion in the ISAR (inverse synthetic aperture radar) images from moving targets. Proceedings of IEEE International Conference on Image Processing (ICIP '04), October 2004, Singapore 1: 25–28.

    Google Scholar 

  6. Thayaparan T, Lampropouols G, Wong SK, Riseborough E: Application of adaptive joint time-frequency algorithm for focusing distorted ISAR images from simulated and measured radar data. IEE Proceedings - Radar, Sonar and Navigation 2003, 150(4):213–220. 10.1049/ip-rsn:20030670

    Article  Google Scholar 

  7. Katkovnik V: A new form of the Fourier transform for time-varying frequency estimation. Signal Processing 1995, 47(2):187–200. 10.1016/0165-1684(95)00107-7

    Article  MathSciNet  Google Scholar 

  8. Katkovnik V: Local polynomial periodogram for time-varying frequency estimation. South African Statistical Journal 1995, 29(2):169–198.

    MathSciNet  MATH  Google Scholar 

  9. Stanković LJ, Djukanović S: Order adaptive local polynimial FT based interference rejection in spread spectrum communication systems. Proceedings of IEEE International Symposium on Intelligent Signal Processing (WISP '03), September 2003, Budapest, Hungary

    Google Scholar 

  10. Baraniuk RG, Flandrin P, Jensen AJEM, Michel OJJ: Measuring time-frequency information content using Rényi entropy. IEEE Transactions on Information Theory 2001, 47(4):1391–1409. 10.1109/18.923723

    Article  MathSciNet  Google Scholar 

  11. Stanković LJ: A measure of some time-frequency distributions concentration. Signal Processing 2001, 81(3):621–631. 10.1016/S0165-1684(00)00236-X

    Article  Google Scholar 

  12. Sang T-H, Williams WJ: Rényi information and signal-dependent optimal kernel design. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '95), May 1995, Detroit, Mich, USA 2: 997–1000.

    Google Scholar 

  13. Djurović I, Stanković LJ: Moments of multidimensional polynomial FT. IEEE Signal Processing Letters 2004, 11(11):879–882. 10.1109/LSP.2004.836947

    Article  Google Scholar 

  14. Daković M, Djurović I, Stanković LJ: Adaptive local Fourier transform. Proceedings of the 11th European Signal Processing Conference (EUSIPCO '02), September 2002, Toulouse, France 2: 603–606.

    Google Scholar 

  15. Wei Y, Bi G: Efficient analysis of time-varying multi-component signals with modified LPTFT. EURASIP Journal on Applied Signal Processing 2005, 2005(8):1261–1268. 10.1155/ASP.2005.1261

    MATH  Google Scholar 

  16. Pitas I, Venetsanopoulos AN: Nonlinear Digital Filters: Principles and Applications. Kluwer Academic, Boston, Mass, USA; 1990.

    Book  Google Scholar 

  17. Djurović I, Stanković LJ, Böhme JF: Robust L-estimation based forms of signal transforms and time-frequency representations. IEEE Transactions on Signal Processing 2003, 51(7):1753–1761. 10.1109/TSP.2003.812739

    Article  MathSciNet  Google Scholar 

  18. Allen JB, Rabiner LR: A unified approach to short-time Fourier analysis and synthesis. Proceedings of the IEEE 1977, 65(11):1558–1564.

    Article  Google Scholar 

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Correspondence to Igor Djurović.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Djurović, I., Thayaparan, T. & Stanković, L. Adaptive Local Polynomial Fourier Transform in ISAR. EURASIP J. Adv. Signal Process. 2006, 036093 (2006). https://doi.org/10.1155/ASP/2006/36093

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