Progress In Electromagnetics Research M
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By X. Zhang, J. Cai, L. Liu, and Y. Yang

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A regular cross terms algorithm is derived for the parameter estimation of the multi-component polynomial phase signals in additive white Gaussian noise. The basic idea is first to separate its phase parameters into two sets by nonlinear procedures£¬and then each set has half of the parameters in its auto-terms. Furthermore, using two linear transforms to deal with the two signals respectively, the phase coefficients of cross terms can be regulated for the identification and elimination of false peaks caused by the cross terms. Simulations are presented to illustrate the performance of the proposed algorithm.

X. Zhang, J. Cai, L. Liu, and Y. Yang, "Detection and Estimation of Multi-Component Polynomial Phase Signals by Constructing Regular Cross Terms," Progress In Electromagnetics Research M, Vol. 20, 143-153, 2011.

1. Lim, K.-S. and V. C. Koo, "Design and construction of wideband Vna ground-based radar system with real and synthetic aperture measurement capabilities," Progress In Electromagnetics Research, Vol. 86, 259-275, 2008.

2. Sabry, R. and P. W. Vachon, "Advanced polarimetric synthetic aperture radar (SAR) and electro-optical (Eo) data fusion through unified coherent formulation of the scattered EM field," Progress In Electromagnetics Research, Vol. 84, 189-203, 2008.

3. Zhao, Y. W., M. Zhang, and H. Chen, "An effcient ocean SAR raw signal simulation by employing fast Fourier transform," Journal of Electromagnetic Waves and Applications, Vol. 24, No. 16, 2273-2284, 2010.

4. Grouffaud, J., P. Larzabal, A. Ferreol, and H. Clergeot, "Adaptive maximum likelihood algorithms for the blind tracking of time-varying multipath channels," International Journal of Adaptive Control and Signal Processing, Vol. 12, No. 2, 207-222, 1998.

5. Ikram, M. Z. and G. Tong Zhou, "Estimation of multicomponent polynomial phase signals of mixed orders," Signal Processing, Vol. 81, No. 11, 2293-2308, Nov. 2001.

6. Ferrari, A., C. Theys, and G. Alengrin, "Polynomial-phase signal analysis using stationary moments," Signal Processing, Vol. 54, No. 3, 239-248, Nov. 1996.

7. Angeby, J., "Estimating signal parameters using the nonlinear instantaneous least squares approach," IEEE Trans. Signal Process., Vol. 48, No. 10, 2721-2732, Oct. 2000.

8. Wu, Y., H. C. So, and H. Liu, "Subspace-based algorithm for parameter estimation of polynomial phase signals," IEEE Trans. Signal Process., Vol. 56, No. 10, Oct. 2008.

9. Peleg, S. and B. Porat, "Estimation and classification of polynomial phase signals," IEEE Trans. Inf. Theory, Vol. 37, 422-431, Mar. 1991.

10. Wang, Y. and G. Zhou, "On the use of high-order ambiguity function for multi-component polynomial phase signals," Signal Processing, Vol. 65, No. 2, 283-296, Mar. 1998.

11. Wang, Y. and Y. C. Jiang, "New time-frequency distribution based on the polynomial Wigner-Ville distribution and L class of Wigner-Ville distribution," IET Signal Process., Vol. 4, No. 2, 130-136, 2010.

12. Pham, D. S. and A. M. Zobir, "Analysis of multicomponent polynomial phase signals," IEEE Trans. Signal Process., Vol. 55, No. 1, Jan. 2007.

13. Barbarossa, S., A. Scaglione, and G. B. Giannakis, "Product high-order ambiguity function for multicomponent polynomial-phase signal modeling," IEEE Trans. Signal Process., Vol. 46, 691-708, Mar. 1998.

14. Barkat, B. and B. Boashash, "Design of higher order polynomial Wigner-Ville distributions," IEEE Trans. Signal Process., Vol. 47, No. 9, 2608-2611, Sep. 1999.

15. Viswanath, G. and T. V. Sreenivas, "IF estimation using higher order TFRs," Signal Processing, Vol. 82, No. 2, 127-132, Feb. 2000.

16. O'Shea, P. and R. A. Wiltshire, "A new class of multilinear functions for polynomial phase signal analysis," IEEE Trans. Signal Process., Vol. 57, No. 6, Jun. 2009.

17. Cornu, C., S. Stankovic, C. Ioana, A. Quinquis, and L. Stankovic, "Generalized representation of phase derivatives for regular signals," IEEE Trans. Signal Process., Vol. 55, No. 10, 4831-4838, Oct. 2007.

18. Wang, P., I. Djurovic, and J. Yang, "Generalized high-order phase function for parameter estimation of polynomial phase signal," IEEE Trans. Signal Process., Vol. 54, No. 7, 3023-3028, Jul. 2008.

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