基于压缩感知的脉冲超宽带信号检测
发布时间：2018-10-17 10:38
【摘要】：传统的信号检测算法基于奈奎斯特采样定理来实现,这对于带宽极宽的超宽带(ultra-wideband,UWB)信号而言由于要求采样速率过高而很难用硬件去实现。为此,本文研究了基于压缩感知(compressive sensing,CS)的脉冲超宽带(impulse radio UWB,IR-UWB)信号检测问题,利用IR-UWB信号在时域上的稀疏特性,设计了一种基于压缩感知的IR-UWB信号检测框架,在此基础上提出了一种自适应加权正交匹配追踪检测算法。仿真结果表明,新算法不仅能够通过远少于奈奎斯特定理所要求的采样速率检测出IR-UWB信号,而且与基于匹配追踪的压缩感知检测算法相比,新算法在低信噪比的情况下对IR-UWB信号的检测效果更佳。
[Abstract]:The traditional signal detection algorithm is based on Nyquist sampling theorem, which is difficult to implement in hardware for ultra-wideband (ultra-wideband,UWB) signals with wide bandwidth due to the high sampling rate. Therefore, the problem of pulse ultra-wideband (impulse radio UWB,IR-UWB) signal detection based on compression sensing (compressive sensing,CS) is studied in this paper. Based on the sparse characteristic of IR-UWB signal in time domain, a IR-UWB signal detection framework based on compressed sensing is designed. On this basis, an adaptive weighted orthogonal matching tracking detection algorithm is proposed. Simulation results show that the proposed algorithm not only detects IR-UWB signals at a much lower sampling rate than that required by Nyquist theorem, but also compares with the compression sensing detection algorithm based on matching tracking. The new algorithm is better for IR-UWB signal detection under low signal-to-noise ratio (SNR).
【作者单位】： 宁波大学通信技术研究所;
【基金】：国家自然科学基金(61301152,61071119) 浙江省教育厅科研项目(201224625) 宁波市自然科学基金(2012A610017,2013A610117) 宁波市科技创新团队研究计划(2011B81002)
【分类号】：TN925
[Abstract]:The traditional signal detection algorithm is based on Nyquist sampling theorem, which is difficult to implement in hardware for ultra-wideband (ultra-wideband,UWB) signals with wide bandwidth due to the high sampling rate. Therefore, the problem of pulse ultra-wideband (impulse radio UWB,IR-UWB) signal detection based on compression sensing (compressive sensing,CS) is studied in this paper. Based on the sparse characteristic of IR-UWB signal in time domain, a IR-UWB signal detection framework based on compressed sensing is designed. On this basis, an adaptive weighted orthogonal matching tracking detection algorithm is proposed. Simulation results show that the proposed algorithm not only detects IR-UWB signals at a much lower sampling rate than that required by Nyquist theorem, but also compares with the compression sensing detection algorithm based on matching tracking. The new algorithm is better for IR-UWB signal detection under low signal-to-noise ratio (SNR).
【作者单位】： 宁波大学通信技术研究所;
【基金】：国家自然科学基金(61301152,61071119) 浙江省教育厅科研项目(201224625) 宁波市自然科学基金(2012A610017,2013A610117) 宁波市科技创新团队研究计划(2011B81002)
【分类号】：TN925
【参考文献】
相关期刊论文 前2条
1 顾福飞;池龙;张群;罗迎;朱丰;;稀疏阵列L型MIMO雷达运动目标三维成像方法[J];微波学报;2012年03期
2 陈思思;李跃华;陈昆;;基于压缩感知的毫米波一维距离像算法研究[J];微波学报;2012年S1期
相关博士学位论文 前1条
1 石磊;压缩感知在超宽带信道估计中的应用研究[D];北京邮电大学;2011年
【共引文献】
相关期刊论文 前2条
1 高磊;曾勇虎;郑光勇;;MIMO雷达成像研究现状与发展趋势[J];航天电子对抗;2013年04期
2 张进;齐世友;毛云祥;;基于稀疏恢复的循环平稳信号DOA估计[J];微波学报;2013年03期
相关博士学位论文 前2条
1 孙璇;基于压缩感知的认知无线电频谱感知算法研究[D];北京邮电大学;2012年
2 李德建;压缩感知与超宽带信道建模的研究[D];北京邮电大学;2012年
相关硕士学位论文 前2条
1 王彦腾;基于模糊模式识别和遗传算法的脉冲超宽带目标识别方法理论研究[D];北京邮电大学;2013年
2 吴浩;基于随机解调的压缩采样与波形重构的实现[D];电子科技大学;2013年
【二级参考文献】
相关期刊论文 前10条
1 梁朝晖,周正;基于小波的超宽带脉冲波形设计[J];北京邮电大学学报;2005年03期
2 郭彩丽;张天魁;曾志民;冯春燕;;认知无线电关键技术及应用的研究现状[J];电信科学;2006年08期
3 马志W，
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