基于STFT的无人机跳频信号检测与参数估计  

Frequency Hopping Signal Detection and Parameter Estimation for UAV Based on STFT

作　　者：徐韬 卢联超 位小记 吉彦军 张俊威 XU Tao;LU Lianchao;WEI Xiaoji;JI Yanjun;ZHANG Junwei(Jiaxing Vocational and Technical College,Jiaxing,Zhejiang 314036,China)

机构地区：[1]嘉兴职业技术学院,浙江嘉兴314036

出　　处：《自动化应用》2023年第3期6-9,共4页Automation Application

基　　金：浙江省大学生科技创新活动计划(2022R470A003);嘉兴市公益性研究计划项目(2022AD10025)。

摘　　要：为了有效实现对无人机的监管,避免涉密、干扰航班、扰民等事件发生,需快速识别出监测范围内的无人机信号,为此提出一种基于STFT的无人机跳频信号检测与参数估计方法。该技术对接收的信号样本做STFT变换,在时频图上采用时频能量对消法实现无人机跳频信号的盲检测,并在此基础上设计一种自适应的形态学滤波器消除干扰,同时引入最小二乘估计算法提升无人机跳频信号参数估计的性能。通过实验测试表明,算法在SNR不低于6dB时,无人机跳频信号的检测概率在95%以上,且能正确估计出无人机跳频信号的跳频周期、跳频起跳时刻和跳频频率集等参数,实用性较强,工程使用价值较高。In order to effectively supervise UAVs and avoid incidents involving secrets,interfering with flights,disturbing people,etc.,it is necessary to quickly identify the UAV signals within the monitoring range,therefore,a frequency hopping signal detection and parameter estimation method based on STFT for UAV is proposed.Firstly,the received signal samples are transformed by STFT,and blind detection of UAV frequency hopping signal is realized by using time-frequency energy cancellation method on time-frequency diagram.On this basis,an adaptive morphological filter is designed to eliminate interference,and the least square estimation is introduced to improve the performance of UAV frequency hopping signal parameter estimation.The experimental test shows that when the SNR of the algorithm is not less than 6 dB,the detection probability of the UAV frequency hopping signal is more than 95%,and the algorithm can correctly estimate the parameters of the UAV frequency hopping signal,such as the frequency hopping cycle,the frequency hopping take-off time,and the frequency hopping set.The algorithm has strong practicability and high engineering value.

关 键 词：短时傅里叶变换(STFT) 时频对消 形态学滤波 

分 类 号：TN911.7[电子电信—通信与信息系统]