能量检测及特征值全盲检测的改进算法  

An improved algorithm for energy detection and full blind detection of eigenvalue

作　　者：吴晋 廖艳苹[1] WU Jin;LIAO Yanping(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨150001

出　　处：《应用科技》2023年第4期66-70,共5页Applied Science and Technology

基　　金：国家重点研发计划项目(2018YFE0206500)。

摘　　要：为解决能量检测算法既需要噪声功率的先验信息且在低干噪比下检测性能较差的问题,本文通过构建错误概率函数对能量检测算法做出改进;同时为克服噪声功率不确定性带来的影响,在基于特征值的全盲检测算法中,提出加权融合算法,明显提高检测性能。仿真结果表明:在低干噪比时,改进的能量检测算法检测概率提高了约0.4;在缺乏先验条件时,基于特征值检测的加权融合检测算法在保证恒虚警概率的同时检测概率提高了约0.15。In order to solve the problem that the energy detection algorithm not only needs prior information of noise power,but also has poor detection performance at low interference-to-noise ratio,this paper improves the energy detection algorithm by constructing an error probability function.At the same time,in order to overcome the impact of uncertain noise power,in the blind detection algorithm based on eigenvalues,the weighted fusion detection is proposed,which significantly improves the detection probability.The simulation results show that the detection probability of the improved energy detection algorithm can be effectively improved by approximately 0.4 at low interference-to-noise ratio.In the absence of a priori condition,the detection probability of weighted fusion detection algorithm based on eigenvalue detection has been improved by approximately 0.15 while maintaining the constant false-alarm rate.

关 键 词：干扰检测 能量检测 全盲检测 加权融合检测 北斗卫星导航系统 虚警概率 检测概率 错误概率函数 

分 类 号：TN971.1[电子电信—信号与信息处理]