非协调通信信号自动调制识别系统研究
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摘要
同频频率和杂波辐射频率干扰对传统系统精准识别影响较大,为了解决该问题,提出了非协调通信信号自动调制识别系统设计。架构总体结构框图,使用TMS320VC5510A型号芯片设计DSP数字信号处理器,并对内部连接示意图进行分析,使信号顺利传递到处理器中。设计流水线结构转换方式,避免杂波辐射频率干扰。面向DSP处理器对软件功能模块展开设计,分析信号管理模式与调制机制,实现多线程通信。判断多线程通信信号似然度,并跟踪,根据跟踪结果对信号进行识别。通过对比结果可知,该系统最高识别精准度可达到95%,具有较好识别能力。
In order to solve the problem,an automatic modulation recognition system for uncoordinated communication signals is designed to solve the problem. The overall structure block diagram,the use of TMS320VC5510 A model chip to design DSP digital signal processor,and the analysis of the internal connection diagram,so that the signal is successfully transferred to the processor. The transformation mode of pipeline structure is designed to avoid clutter radiation frequency interference. The DSP processor is applied to design the software function module,and analyze the signal management mode and modulation mechanism to achieve multithreaded communication. The likelihood of multithreading communication signals is judged and tracked,and the signals are identified based on tracking results. By comparing the results,we can see that the highest recognition accuracy of the system can reach 95%,and it has good recognition ability.
In order to solve the problem,an automatic modulation recognition system for uncoordinated communication signals is designed to solve the problem. The overall structure block diagram,the use of TMS320VC5510 A model chip to design DSP digital signal processor,and the analysis of the internal connection diagram,so that the signal is successfully transferred to the processor. The transformation mode of pipeline structure is designed to avoid clutter radiation frequency interference. The DSP processor is applied to design the software function module,and analyze the signal management mode and modulation mechanism to achieve multithreaded communication. The likelihood of multithreading communication signals is judged and tracked,and the signals are identified based on tracking results. By comparing the results,we can see that the highest recognition accuracy of the system can reach 95%,and it has good recognition ability.
引文
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[16]凌青,张立民,闫文君,等.频率选择信道下STBC-OFDM信号盲识别[J].系统工程与电子技术,2017,39(5):1141-1147.
[2]刘莹,单洪,胡以华,等.基于谱分析的卫星通信调制识别算法[J].火力与指挥控制,2017,42(1):45-48.
[3]沈连腾,巩克现,王伟年,等. VHF/UHF常用通信信号调制识别算法[J].计算机仿真,2017,34(1):174-179.
[4]王兰勋,郭淑婷,贾层娟.基于小波包络差异性的数字调制方式识别技术[J].电子技术应用,2017,43(2):95-98.
[5]许程成,张剑云,黄健航,等.基于DBN的频率与相位编码信号快速调制识别方法[J].现代雷达,2018,33(2):33-39.
[6]丁锡龙,金乾坤.基于深度神经网络的数字信号调制类型自动识别方法[J].湘潭大学自科学报,2017,39(3):70-74.
[7]刘明骞,李建英,李兵兵,等.认知无线电Underlay模式下MQAM信号的调制识别[J].西安交通大学学报,2018,24(2):52-57.
[8]杨伟超,杨新权. Alpha稳定分布噪声下卫星双信号调制识别[J].应用科学学报,2017,35(3):309-316.
[9]田海丽,田猛.无线光纤通信中双重调制系统设计[J].激光杂志,2017,38(10):77-80.
[10]韩洁,张涛,王欢欢,等.基于3D-Hibert能量谱和多尺度分形特征的通信辐射源个体识别[J].通信学报,2017,38(4):99-109.
[11]杨莉,胡国兵.一种改进的BPSK/QPSK信号调制识别算法[J].电讯技术,2017,57(8):896-902.
[12]崔潇田,高勇.利用指数范数的QAM信号调制识别方法[J].电讯技术,2017,57(11):1278-1282.
[13]王飞,于凤芹.结合多尺度时频调制与多线性主成分分析的乐器识别[J].计算机应用,2018,38(3):891-894.
[14]谭晓衡,褚国星,张雪静,等.基于高阶累积量和小波变换的调制识别算法[J].系统工程与电子技术,2018,18(1):171-177.
[15]黄波,潘爽,李雪.基于四阶循环平稳的STBC-OFDM信号盲识别[J].信号处理,2017,33(9):1221-1229.
[16]凌青,张立民,闫文君,等.频率选择信道下STBC-OFDM信号盲识别[J].系统工程与电子技术,2017,39(5):1141-1147.