基于特征值融合的动态信道化子带检测算法  

Dynamic channelized subband detection algorithm based on eigenvalue fusion

作　　者：陈侯伯 刘霖 崔宁 张旭冉 赵麒瑞 刘翔 CHEN Houbo;LIU Lin;CUI Ning;ZHANG Xuran;ZHAO Qirui;LIU Xiang(Aerospace Information Innovation Institute,Chinese Academy of Sciences,Beijing 100094,China;School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China;School of Information Science and Technology,Fudan University,Shanghai 200433,China)

机构地区：[1]中国科学院空天信息创新研究院,北京100094 [2]中国科学院大学电子电气与通信工程学院,北京100049 [3]复旦大学信息科学与工程学院,上海200433

出　　处：《系统工程与电子技术》2025年第2期360-368,共9页Systems Engineering and Electronics

基　　金：国家自然科学基金(61971026)资助课题。

摘　　要：针对动态数字信道化接收领域中传统子带检测算法需要信号和噪声先验信息等问题,提出基于特征值融合的动态信道化子带检测算法。首先,基于随机矩阵理论(random matrix theory, RMT),利用采样协方差矩阵中的最大、最小和平均特征值,引入融合参数α,构造融合检测统计量。随后,通过最小特征值的极限分布,推导出一种高效的检测门限,并据此设计一套基于特征值融合的子带盲检测算法,命名为α-最大、最小和平均特征值(α-maximum-average-minimum eigenvalue, α-MAME)算法。在实验阶段,对不同动态数字信道化接收条件下的算法性能进行仿真验证。结果表明,与现有算法相比,所提子带检测算法在低信噪比和低维度条件下具有更好的检测性能。To address issues in traditional subband detection algorithms in the field of dynamic digital channelized reception field,such as the need for prior information about signals and noise.An eigenvalue fusion based dynamic channel subband detection algorithm is proposed.Firstly,based on random matrix theory(RMT),the maximum,minimum,and average feature values in the sampled covariance matrix are employed,incorporating a fusion parameterαto construct a fusion detection statistical value.Subsequently,an efficient detection threshold is derived through the limit distribution of the minimum feature value.Based on this,a subband blind detection algorithm based on feature-value fusion is designed,which is named as theα-maximum-average-minimum eigenvalue(α-MAME)algorithm.In the experiment,the algorithm’s performance is simulated and verified under various receiving conditions of dynamic digital channels.The experimental results indicate that compared to existing algorithms,the proposed subband detection algorithm demonstrates superior detection performance under low signal-to-noise ratios and low-dimensional conditions.

关 键 词：动态数字信道化 子带检测 特征值检测 随机矩阵 

分 类 号：TN911.7[电子电信—通信与信息系统]