利用时频稀疏性的跳频信号盲检测和参数盲估计  

Blind Detection and Parameter Estimation of Frequency Hopping Signals with Time-frequency Sparsity

作　　者：王琳[1] 赵知劲[1,2] 金昊炫 WANG Lin;ZHAO Zhi-jin;JIN Hao-xuan(School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China;State Key Lab of Information Control Technology in Communication System,the 36th Research Institute of China Electronics Technology Group Corporation,Jiaxing,Jiaxing 314001,China;Soyea Technology Co.,Ltd,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学通信工程学院,杭州310018 [2]中国电子科技集团第36研究所通信系统信息控制技术国家级重点实验室,浙江嘉兴314001 [3]数源科技股份有限公司,杭州310018

出　　处：《火力与指挥控制》2021年第10期126-130,共5页Fire Control & Command Control

基　　金：国家自然科学基金资助项目(U19B2016)。

摘　　要：针对在低信噪比的稳定分布噪声和定频干扰背景中,跳频信号检测和参数估计性能不佳的问题,利用分数低阶短时傅里叶变换得到时频矩阵;对时频矩阵按频率行去均值,抑制定频干扰;通过时频峰值优化、时频矩阵清洗和强化处理,降低频谱泄漏和噪声对跳频信号时频稀疏性的影响;利用此稀疏性进行检测和估计,即根据跳频信号在驻留时间内的连续性检测跳频信号,估计跳频频率;根据驻留时间起点及间隔,估计跳变时刻和跳周期。仿真结果表明,在低信噪比下,该算法的检测和参数估计性能均有较大提高,且优于现有算法。In view of the poor performance of frequency-hopping signal detection and parameter estimation under the conditions of stable distribution with low signal-to-noise ratio and fixed frequency interference,a fractional low-order short-time Fourier transform is used to obtain a time-frequency matrix.The mean is removed from time-frequency matrix according to frequency line The fixed-frequency interferences are supposed.Then time-frequency peak optimization,time-frequency matrix cleaning and enhancement are processed to reduce the effect of spectrum leakage and noise on the time-frequency sparsity of frequency-hopping signal.Finally,the sparsity of the frequency-hopping signal is used for detection and estimation of hopping-frequencies according to its continuity of the frequency-hopping signal during the residence time.Finally,the hopping-time and hopping-period are estimated according to the starting point and interval of the dwell time.The simulation results show that the performance of detection and parameter estimation of this algorithm is greatly improved under the low signal-to-noise ratio,the proposed algorithm is superior to the existing algorithms.

关 键 词：稳定分布 跳频检测 参数估计 分数低阶STFT 

分 类 号：TN911.7[电子电信—通信与信息系统]