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UWB signal detection based on wavelet packet and FHN model

机译:基于小波包和FHN模型的UWB信号检测

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In UWB-IR signal detection, the threshold of signal to noise ratio(SNR) limit the performance of FHN model detection method, from this point, wavelet packet is introduced into FHN model, a novel UWB-IR signal detection method based on wavelet packet and FHN model is proposed, in addition, the disadvantages of traditional single threshold wavelet packet is analyzed, combined with the new piecewise threshold wavelet packet and FHN model to detect UWB-IR signal. Furthermore, the performance of the proposed algorithm is simulated and analyzed. Simulation results shows that the proposed algorithm overcome the SNR threshold of FHN model detection method, the detection performance of FHN model is improved. Therefore, the UWB-IR signal can be detected effectively under strong noise.
机译:在UWB-IR信号检测中,信噪比(SNR)阈值限制了FHN模型检测方法的性能,从这一点出发,将小波包引入到FHN模型中,这是一种基于小波包的新型UWB-IR信号检测方法。提出了FHN模型,并分析了传统的单阈值小波包的缺点,并结合新的分段阈值小波包和FHN模型对UWB-IR信号进行了检测。此外,对所提出算法的性能进行了仿真和分析。仿真结果表明,该算法克服了FHN模型检测方法的信噪比阈值,提高了FHN模型的检测性能。因此,可以在强噪声下有效地检测UWB-IR信号。

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