Cubic-phase function evaluation for multicomponent signals with application to SAR imaging

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Cubic-phase function evaluation for multicomponent signals with application to SAR imaging

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A cubic-phase function evaluation technique for multicomponent frequency-modulated signals with non-overlapped components in the time–frequency (TF) plane is proposed. The proposed technique is based on the short-time Fourier transform. Cross-terms are removed or reduced in the same manner as in the case of the TF representation called the S-method. The proposed technique is applied for visualisation of signals in time-chirp-rate plane and parameter estimation of analytical and radar signals. In addition, a procedure for focusing SAR images by using estimated parameters is proposed in order to verify obtained results.

Inspec keywords: Fourier transforms; radar imaging; function evaluation; parameter estimation; synthetic aperture radar; time-frequency analysis

Other keywords: multicomponent frequency-modulated signals; parameter estimation; cubic-phase function evaluation technique; short-time Fourier transform; time-frequency plane; time-chirp-rate plane; SAR imaging; signal visualisation; synthetic aperture radar; S-method

Subjects: Radar equipment, systems and applications; Optical, image and video signal processing; Functional analysis (numerical analysis); Integral transforms in numerical analysis

References

    1. 1)
      • L.J. Stanković . A method for time–frequency signal analysis. IEEE Trans. Signal Process. , 42 , 225 - 229
    2. 2)
      • J.J. Sharma , C.H. Gierull , M.J. Collins . Compensating the effects of target acceleration in dual-channel SAR-GMTI. IEE Proc. Radar, Sonar Navig. , 153 , 53 - 62
    3. 3)
      • L.J. Stanković , B. Boashash . (2003) Quadratic and higher order time–frequency analysis based on the STFT, Time–frequency signal analysis and processing.
    4. 4)
      • Wang, P., Djurović, I., Yang, J.: `Instantaneous frequency rate estimation based on robust cubic phase function', Proc. Int. Conf. Acoustics, Speech, and Signal Processing, May 2006, Toulouse, France, p. 89–92.
    5. 5)
      • R.C. Gonzales , R.E. Woods . (1993) Digital image processing.
    6. 6)
      • V.C. Chen , H. Ling . (2002) Time–frequency transforms for radar imaging and signal analysis.
    7. 7)
      • P. O'Shea . A new technique for instantaneous frequency rate estimation. IEEE Signal Process. Lett. , 9 , 251 - 252
    8. 8)
      • M. Farquharson , P. O'Shea . Extending the performance of the cubic phase function algorithm. IEEE Trans. Signal Process. , 55 , 4767 - 4774
    9. 9)
      • M. Farquharson , P. O'Shea , G. Ledwich . A computationally efficient technique for estimating the parameters of polynomial phase signals from noisy observations. IEEE Trans. Signal Process. , 53 , 3337 - 3342
    10. 10)
      • D.C. Reid , A.M. Zoubir , B. Boashash . Aircraft flight parameter estimation based on passive acoustic techniques using the polynomial Wigner–Ville distribution. J. Acoust. Soc. Amer. , 1 , 207 - 223
    11. 11)
      • S. Peleg , B. Friedlander . The discrete polynomial phase transform. IEEE Trans. Signal Process. , 43 , 1901 - 1914
    12. 12)
      • M.D. Desai , W.K. Jenkins . Convolution backprojection image reconstruction for spotlight mode synthetic aperture radar. IEEE Trans. Image Process. , 1 , 505 - 517
    13. 13)
      • F. Hlawatsch , G.F. Boudreaux-Bartels . Linear and quadratic time–frequency signal representations. IEEE Signal Process. Mag. , 9 , 21 - 67
    14. 14)
      • L.J. Stanković , T. Thayaparan , V. Popović , M. Djurović , M. Daković . Adaptive S-method for SAR/ISAR imaging. EURASIP J. Adv. Signal Process.
    15. 15)
      • Xiao, S., Munson, D.C., Basu, S., Bresler, Y.: `An ', Conf. Rec. of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers, October 2000, Pacific Grove, CA, USA, p. 3–7, (1).
    16. 16)
      • J. Jeong , W.J. Williams . Mechanism of the cross-terms in spectrograms. IEEE Trans. Signal Process. , 40 , 2608 - 2613
    17. 17)
      • P. O'Shea . A fast algorithm for estimating the parameters of a quadratic FM signal. IEEE Trans. Signal Process. , 52 , 385 - 393
    18. 18)
      • B. Porat . (1994) Digital processing of random signals: theory and methods.
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