基于构造相关器的脉内调制识别方法  

Intra-pulse Modulation Analysis Algorithm Based on Constructed Correlator

在线阅读下载全文

作  者:王显跃 熊波 任圣君 史剑虹 WANG Xianyue;XIONG Bo;REN Shengjun;SHI Jianhong(Southwest China Research Institute of Electronic Equipment,Chengdu 610036,China)

机构地区:[1]中国电子科技集团公司第二十九研究所,成都610036

出  处:《电子信息对抗技术》2022年第5期28-33,共6页Electronic Information Warfare Technology

摘  要:脉内分析算法对电子对抗侦察设备采集的雷达信号中频数据进行分析,识别脉内调制类型,提取调制参数,获得信号情报并支撑后续干扰策略选择。针对传统脉内调制类型识别方法大多基于时间频率及时间相位特征,未充分利用信号自相关前后脉冲宽度比及波形特征的问题,提出基于信号相关的脉内调制识别方法。通过接收信号带宽估计及有限冲激响应(Finite Impulse Response,FIR)滤波构造相关器对信号进行相关,不同调制信号得到了不同相关前后脉宽比及不同波形振荡特征。理论推导及仿真结果表明,将相关后信号特征运用于脉内分析,可简化识别流程,减小计算量并提高识别准确率。Intra-pulse analysis algorithm is used to analyze radar signal intermediate frequency data collected by electronic warfare reconnaissance facility,and the modulation type could be recognized,the modulation parameters could be extracted.The obtained information is used to support jamming strategy choosing.The traditional intra-pulse modulation type recognition methods are mostly based on the characteristics of time frequency and time phase.The pulse width ratio and waveform characteristics before and after signal autocorrelation are not fully utilized.The intra-pulse analysis algorithm based on signal correlation is advized.The received signal bandwidth estimation and correlator constructed by Finite Impulse Response(FIR)filter are used to correlate the signal.The pulse width ratio before and after correlation and the oscillation characteristics of different waveforms are different for different modulation signals.Theoretical derivation and simulation results show that the identification process is simplified,the amount of calculation is reduced and the recognition accuracy is improved,when correlation signal features are used for intra-pulse analysis.

关 键 词:雷达 电子侦察 脉内分析 调制识别 相关 压缩比 

分 类 号:TN971.1[电子电信—信号与信息处理]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象