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.
doi:10.2528/PIER08092204 Google Scholar
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.
doi:10.2528/PIER08071005 Google Scholar
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.
doi:10.1163/156939310793699064 Google Scholar
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.
doi:10.1002/(SICI)1099-1115(199803)12:2<207::AID-ACS488>3.0.CO;2-H Google Scholar
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.
doi:10.1016/S0165-1684(01)00095-0 Google Scholar
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.
doi:10.1016/S0165-1684(96)00110-7 Google Scholar
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. Google Scholar
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. Google Scholar
9. Peleg, S. and B. Porat, "Estimation and classification of polynomial phase signals," IEEE Trans. Inf. Theory, Vol. 37, 422-431, Mar. 1991.
doi:10.1109/18.75269 Google Scholar
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.
doi:10.1016/S0165-1684(97)00224-7 Google Scholar
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.
doi:10.1049/iet-spr.2009.0026 Google Scholar
12. Pham, D. S. and A. M. Zobir, "Analysis of multicomponent polynomial phase signals," IEEE Trans. Signal Process., Vol. 55, No. 1, Jan. 2007.
doi:10.1109/TSP.2006.882085 Google Scholar
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.
doi:10.1109/78.661336 Google Scholar
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.
doi:10.1109/78.782225 Google Scholar
15. Viswanath, G. and T. V. Sreenivas, "IF estimation using higher order TFRs," Signal Processing, Vol. 82, No. 2, 127-132, Feb. 2000.
doi:10.1016/S0165-1684(01)00168-2 Google Scholar
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.
doi:10.1109/TSP.2009.2014811 Google Scholar
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.
doi:10.1109/TSP.2007.896280 Google Scholar
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. Google Scholar