直扩信号的谱检测和神经网络估计

Detection and Estimation of DS/SS Signals by Spectra Analysis and Neural Networks

论述了二次谱理论、谱相关理论和神经网络方法在直接序列扩频 (DS/SS)信号的检测与估计中的应用 ,提出了利用谱分析结合神经网络的方法来实现对低信噪比DS/SS信号的参数及其伪码 (PN)序列的估计。计算机模拟结果表明 ,该方法在较低的输入信噪比条件下能良好地工作。

We focus on the applications of spectra(spectrum-reprocessing and cyclic-spectrum) analysis and neural networks(NN) to detect and estimate the direct sequence spread spectrum(DS/SS) signals, proposing a method by utilizing spectra analysis and neural networks to realize the parameter detection of the lower signal to noise ratios(SNR) DS/SS signals and estimation of its pseudo noise(PN) sequence The computer simulations show that these methods can work well on the lower SNR input signals