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针对现有的基于循环平稳特性的盲检测算法计算复杂、适应信号类型少等问题,提出了一种新的基于循环统计量的盲检测算法。首先给出了基于循环平稳的盲检测机制,进而推导了零假设下检验统计量的渐近分布,避免了复杂的协方差矩阵运算,可得到恒虚警概率下的检测门限;最后为了提高算法对信号类型的稳健性,融合了两种典型的检测器。理论分析和仿真结果验证了新的盲检测算法具有良好的性能。
Aiming at the problems that the existing blind detection algorithms based on cyclostationary characteristics are complex in calculation and have few types of signals, a new blind detection algorithm based on cyclic statistics is proposed. At first, a blind detection mechanism based on cyclostationarity is given, and then the asymptotic distribution of the test statistic under the null hypothesis is derived, which avoids the complicated covariance matrix operation and the detection threshold under the constant false alarm probability. Finally, in order to improve the algorithm The robustness of the signal type incorporates two typical detectors. Theoretical analysis and simulation results verify that the new blind detection algorithm has good performance.