异步条件下对变换域通信系统 (TDCS)信号用特征值分解法可估计基函数序列, 但由于协方差矩阵特征分解的不唯一性, 造成分段得到的特征向量存在标量模糊的缺陷。通过理论分析特征值分解算法, 提出了一种改进算法, 将接收信号的分段周期扩大为基函数周期的 2倍, 通过特征值分解算法得到协方差矩阵的最大特征向量, 用长度为基函数周期的窗口在最大特征向量中滑动, 当窗口的二范数达到最大值时, 即可得到基函数序列。通过实验仿真, 改进算法能够有效克服分段向量出现部分正反号的缺陷, 系统误码性能与同步条件下的系统误码性能基本一致。

The basis function sequence is estimated by using the eigenvalue decomposition method for the Transform Domain Communication System(TDCS) signal under the asynchronous conditions. Because the feature vectors obtained by eigen decomposition covariance matrix are not unique, the segmented feature vectors have defects of scalar fuzzy. An improved algorithm is proposed by theoretical analysis of eigenvalue decomposition algorithm. The segmentation period of received signal is expanded to two times of the basis function cycle. The maximum eigenvector of covariance matrix is obtained by using eigenvalue decomposition algorithm. Sliding the window with a length as the basis function period in the maximum eigenvector, the basis function sequence can be estimated when the two-norm of the window reaches the maximum value. Through the experimental simulation, the improved algorithm can effectively overcome the defects of the partial positive and negative number of the segment vector. The bit error performance of the system is basically the same as that of the system under the condition of synchronization.