改进密度峰聚类的walsh码软扩频盲解扩

针对walsh码软扩频信号盲解扩问题，提出一种改进密度峰聚类算法。该算法在已知伪码周期和码片速率的前提下，对接收数据进行分段处理，得到数据矩阵，随后计算数据点的局部密度和距离较高局部密度数据点的最短距离，最后的采用自动确定聚类中心的密度峰聚类算法估计伪码序列规模数和伪码序列。该算法具有在较低信噪比条件下，实现walsh码软扩频信号盲解扩的特点。仿真结果表明，在信噪比较低时，本文算法能够准确估计伪码序列规模数和伪码序列，且时间复杂度较低。 

Blind estimation of soft spread spectrum signal based on improved density peak clustering

For the problem of the soft spectrum signal pseudo-code sequence was difficult to estimate,a blind estimation method of soft spread spectrum signal was proposed based on improved density peak clustering.On the premise of known pseudo-code cycle and chip rate, the received data was segemented to obtain the data matrix.Then,the local density of the data points and the shortest distance from the data points with higher local density were calculated.Finally,the density peak clustering algorithm was used to automatically determine the cluster center to estimate the pseudo-code size and pseudo-code sequence of walsh soft spread siganl.The proposed algorithm has the characteristics of realizing the blind estimation of soft spread spectrum signal of walsh code under the condition of low SNR.The simulation results show that the proposed algorithm can accurately estiamte the pseudo-code sequence size and pseudo-code sequence when the SNR is slow,and the time conplexity is low.