一种基于CAF的频谱混叠多信号检测算法

A Detecting Algorithm Based on CAF for Overlapping Frequency-Spectrum Multi-Signals

针对多源同频混叠信号检测问题,本文提出了一种基于互模糊函数(Cross Ambiguity Function,CAF)的空间域信号检测算法。该算法首先在二维时延-频移搜索范围内计算多信号情况下的CAF值数组,将频谱混叠的多信号映射在空间域上,然后在分析多信号CAF峰特征的基础上,借鉴图像分割中区域增长法的思想,将CAF峰逐一识别、分割,及迭代循环,以实现多信号的检测。本文采用所提出的算法对同频多信号进行了仿真,给出了在不同信噪比下和不同信号功率比下的多信号检测概率,以及不同门限因子对检测概率和虚警概率的影响。仿真结果表明,该算法能够在低信噪比条件下,有效地对具有一定功率差别的同频多信号进行检测。

For multi-signals detection of overlapping frequency-spectrum from different sources, a space-field detection algorithm is proposed in this paper based on Cross Ambiguity Function （CAF）. Firstly, multi-signals are mapped to space-field through array of the signals＇ CAF calculated in the two dimension searching area of time-delay and frequency-shift. Then, considering the characters of the muhi-signals-CAF lobes and drawing from the idea of region-growing method in image segmentation, the signals are detected with iterative circulations by recognizing and segmenting the CAF lobes in accord with the signals one by one. Simulation is carried out to multi-signals with same frequency by the proposed algorithm. The detection probability curves under different Signal Noise Ratios and different Signal Power Ratios are presented. Likewise, the influence by different threshold coefficients to the detection probability and the fault alarm probability is given. The simulation results indicate that the algorithm may effectively detect different power multi-signals of overlapping frequency-spectrum under low SNR.