A Parameter Estimation Algorithm for Frequency-Hopping Signals with a Stable Noise
Yun-Cheng Yang, Xueli Sun, Zhaogen Zhong · 2018
Aiming at the problem that most frequency-hopping parameters estimation methods based on Gaussian white noise are currently under the stable distributed noise background, the performance is drastically reduced. In this paper, two fractional low-order STFT with different window functions are firstly applied to the frequency-hopping signal to obtain two sets of time-frequency data. Then, two sets of time-frequency data are multiplied to obtain a new time-frequency representation, and finally based on time-frequency analysis. Frequency-hopping parameter estimation method realizes estimation of frequency-hopping parameters. Simulation experiments show that the proposed method effectively suppresses the a stable distribution noise. When α=0.8, GSNR ≥1dB; a=1.5, GSNR ≥0dB, an accurate estimation of the frequency-hopping period can be achieved. At the time of α=1.5, the maximum relative error of the estimation time of the algorithm is 3% lower than the STFT, 1.6% lower than the fractional low-order STFT, and the estimated hopping-frequency is more accurate.