A hybrid optimization method for designing polyphase sequences

• Autorzy: Milewski A. , Szczegielniak D.
• Języki publikacji: EN

Abstrakty

EN

Polyphase sequences which have a low autocorrelation ensure an easily detectable peak in the output of a matched filter of a radar receiver. The low autocorrelation for polyphase codes is usually described in terms of the maximum magnitude of its sidelobes level. In this paper, an evolutionary algorithm combined with a local optimizer is used to search for polyphase codes with a small sidelobe level of an aperiodic autocorrelation function. The evolutionary algorithm is based on a floating-point representation and the Gaussian mutation is used to produce offspring for the next generation. The local optimizer is applied to find polyphase sequences which are good starting points for the evolutionary algorithm. This research demonstrates that optimization methods can effectively find polyphase codes with the low autocorrelation and seems to be very promising for future research in area of computer optimization for radar polyphase codes synthesis.

• Wydawca: Polskie Towarzystwo Akustyczne. Oddział Gdański
• Czasopismo: Hydroacoustics
• Rocznik: 2006
• Tom: Vol. 9
• Strony: 125--132
• Opis fizyczny: Bibliogr. 6 poz., rys., tab.

Twórcy

autor

Milewski A.

autor

Szczegielniak D.

• Institute of Telecommunications, University of Technology and Agriculture Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland,

Bibliografia

• [1] M. Friese , H. Zottmann, Polyphase Barker sequences up to length 31,Electron. Lett., 30 (4), 1996.
• [2] N. Levanon, E. Mozeson, Radar Signals, John Wiley & Sons, 100-137, 2004
• [3] N. Mladenović, J. Petrović, V. Kovacević-Vujcić, M. Cangalović, Solving a spread-spectrum radar polyphase code design problem by tabu search and variable neighbourhood search, European Journal of Operations Research, 151:389—399, 2003.
• [4] P. Borwein, R. Ferguson, Polyphase sequences with low autocorrelation, Information Theory, IEEE Transactions on Volume 51, 1564 - 1567, April 2005
• [5] W.Findeisen, J. Szymanowski, A. Wierzbicki, Teoria i metody obliczeniowe optymalizacji,PWN,186-189,Warszawa1977.
• [6] Z. Michalewicz, D. B. Fogel, How to Solve It: Modern Heuristics, Springer Verlag, 276-284, 2000.