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针对网络电磁对抗环境中直接序列扩频信号的伪随机码的估计,这里提出了一种基于神经网络结合信息更新法则的方法,对过去基于神经网络的方法进行改进,构建了新的运算模型。理论分析和计算机仿真结果表明,该方法能在较低的信噪比容限下,正确地估计出扩频信号的伪随机码序列,该方法的性能优于原有的基于神经网络模型的码估计方法,为今后能够解决低信噪比条件下扩频码序列盲处理问题提供了一种更有效的途径。
Aiming at the estimation of pseudo-random codes of direct sequence spread spectrum signals in the network electromagnetic confrontation environment, a method based on neural network combined with information update rule is proposed here. The previous neural network based method is improved and a new operation model is constructed. The theoretical analysis and computer simulation results show that this method can correctly estimate the pseudo-random code sequence of the spread-spectrum signal with lower SNR margin, and its performance is better than that of the original neural network-based code The estimation method provides a more effective way for the future to solve the blind processing problem of the spreading code sequence under the condition of low signal-to-noise ratio.