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实时高精度雷达噪声信号产生方法与FPGA实现 被引量:3
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作者 蔡俊晖 潘明海 《电讯技术》 北大核心 2022年第12期1846-1852,共7页
针对各种典型分布的噪声信号在雷达系统半实物仿真和噪声雷达波形设计中的实际需求,基于Box-Muller算法提出了一种能够实时产生多种分布特性噪声的信号生成方法。首先使用线性反馈移位寄存器产生均匀分布随机序列,然后利用能够实现高精... 针对各种典型分布的噪声信号在雷达系统半实物仿真和噪声雷达波形设计中的实际需求,基于Box-Muller算法提出了一种能够实时产生多种分布特性噪声的信号生成方法。首先使用线性反馈移位寄存器产生均匀分布随机序列,然后利用能够实现高精度、低延迟的坐标旋转数字算法(Coordinate Rotation Digital Computer,CORDIC)实现Box-Muller变换中复杂函数的快速计算,将均匀随机序列转换成高斯分布随机序列,最后利用高斯随机序列经过相关数学运算得到其他复杂分布的随机序列,在此基础上产生具有各种分布特性的噪声信号。基于Xilinx XC7VX415T现场可编程门阵列(Field Programmable Gate Array,FPGA)芯片的实验结果表明,所提方法在保证小数位数据精度为20 b时,可实时产生速率为2.5 Gb/s的高精度随机数据序列,进而生成服从多种函数分布下的噪声信号。所提方法整体资源占用率较少,具有较强的实用性。 展开更多
关键词 雷达系统 数字射频存储器(DRFM) 半实物仿真 雷达噪声信号 Box-Muller算法
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Research on weak signal extraction and noise removal for GPR data based on principal component analysis 被引量:1
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作者 CHEN Lingna ZENG Zhaofa +1 位作者 LI Jing YUAN Yuan 《Global Geology》 2015年第3期196-202,共7页
The ground penetrating radar (GPR) detection data is a wide band signal, always disturbed by some noise, such as ambient random noise and muhiple refleetion waves. The noise affects the target identification of unde... The ground penetrating radar (GPR) detection data is a wide band signal, always disturbed by some noise, such as ambient random noise and muhiple refleetion waves. The noise affects the target identification of underground medium seriously. A method based on principal component analysis (PCA) was proposed to ex- tract the target signal and remove the uncorrelated noise. According to the correlation of signal, the authors get the eigenvalues and corresponding eigenvectors by decomposing the covariance matrix of GPR data and make linear transformation for the GPR data to get the principal components (PCs). The lower-order PCs stand h^r the strong correlated target signals of the raw data, and the higher-order ones present the uneorrelated noise. Thus the authors can extract the target signal and filter uncorrelated noise effectively by the PCA. This method was demonstrated on real ultra-wideband through-wall radar data and simulated GPR data. Both of the results show that the PCA method can effectively extract the GPR target signal and remove the uncorrelated noise. 展开更多
关键词 ground penetrating radar principal component analysis target extraction noise removing
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