摘要
传统的超宽带穿墙雷达数据采样需要满足Nyquist采样定理,超宽带大数据量增大了A/D转换时的硬件压力,压缩感知理论突破了传统Nyquist采样的限制,它是基于信号的稀疏性,测量矩阵的随机性和非线性优化算法来对信号进行压缩采样和重构。文章针对超宽带穿墙雷达的具体工作过程和穿墙雷达目标成像空间的稀疏性提出了一种基于压缩感知理论的成像方法,并通过仿真表明了该方法的可行性和有效性。
The Nyquist sampling theorem must be satisfied in traditional data acquisition of Ultra wideband Through-wall Decection Radar,Ultra-wideband large amount of data increases the problem of A/D hardware,Compressed Sensing（CS） theory is a great breakthrough of traditional Nyquist sampling theory,it accomplishes compressive sampling and recovery of signal based on the sparsity of interested signal,the randomicity of measurement matrix and nonlinearized optimization method.With the specific work process of UWB-TWDR and the sparistiy of the target,a method of imaging with compressive sensing is proposed in this paper,the simulation show that the new imaging method is effective and practical.
出处
《大众科技》
2012年第5期47-49,34,共4页
Popular Science & Technology
基金
国家自然科学基金项目:基于UWB信号的隐藏活动目标自适应检测技术研究(60572054)
关键词
超宽带
压缩感知
测量模型
有效性
Ultra-wideband
compressive sampling
measurement model
effective
