Locating all the Frequency Hopping Components Using Multi-species Particle Swarm Optimization
Автор: Guo Jiantao, Wang Lin
Журнал: International Journal of Computer Network and Information Security(IJCNIS) @ijcnis
Статья в выпуске: 5 vol.3, 2011 года.
Бесплатный доступ
The particle swarm optimization (PSO) algorithm is applied to the problem of blind parameter estimation of frequency hopping signals. For this target, one Time Frequency representation such as Smoothed Pseudo Wigner-Ville Distribution (SPWVD) is computed firstly. Then, the peaks on TF plane are searched using multi-species PSO. Each particle moves around two dimension time and frequency plane and will converge to different species, which seeds represent the centers of frequency hopping components. A numerical study is carried out for signals which are embedded in a very low SNR ratio noise. Results show that the new method is feasible and much more robust than some existing estimation algorithms.
Parameter estimation, particle swarm optimization, frequency hopping signals, time frequency representation
Короткий адрес: https://sciup.org/15011037
IDR: 15011037
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