基于形态学运算的子带频谱检测算法  

Sub-band Spectrum Detection Algorithm Based on Morphological Operation in Complicated Noise Environment

作　　者：李敏乐[1] 毕大平[1] 韩佳辉 

机构地区：[1]解放军电子工程学院,安徽合肥230037

出　　处：《探测与控制学报》2017年第4期49-53,60,共6页Journal of Detection & Control

基　　金：国家自然科学基金项目资助(61171170)

摘　　要：针对现有频谱检测算法无法解决不同信道之间的噪声基底差异的问题,提出了基于形态学运算的双门限自适应子带频谱检测算法。该算法首先利用形态学运算对信道噪声基底进行估计,将其减去后,消除了复杂噪声背景的影响;然后采用自适应双门限频谱检测算法实现子带信号的检测,当检测统计量处于两个门限之间时,采用模糊理论进行判定。仿真结果表明,该算法能够在噪声起伏较大的背景下完成子带信号检测,检测概率优于传统双门限算法和基于差分运算的双门限算法。It is difficult to obtain a good result for the existing spectrum detection algorithms in dynamic digital channelized receiver in complicated noise environment.Aiming at the problem,this paper proposed an adaptive double threshold subband spectrum detection algorithm based on the morphological operation.Firstly,the morphological operations were used to estimate the noise floor of the channel and eliminate the influence of the complex noise environment by subtracting the noise floor.Then,subband signals were detected by using adaptive double threshold spectrum detection algorithm,when the detection quantity was in the two threshold,the fuzzy theory was used to determine the result.Simulation results showed that the proposed algorithm could complete the signal detection in large fluctuation noise environment and obtain a detection probability which superior to the traditional double threshold algorithm and the double threshold algorithm based on differential operation.

关 键 词：噪声背景 动态信道化 频谱感知 形态学运算 模糊理论 

分 类 号：TN911[电子电信—通信与信息系统]