compressdoa

  ：压缩感知是近年来应用数学界提出的一套关于稀疏信号采集和重构的新理论，它突破了传统奈奎斯特采样定理 的限制，以远少于传统奈奎斯特采样定理所需的测量数据就能够精确恢复原信号或估计信号的相关参数。将压缩感知理论应 用到DOA估计，可以解决传统DOA估计中高采样率、以及较多辐射源信号条件下难以定位的限制。研究了基于压缩感知理 论的DOA估计方法，并利用MATLAB进行仿真，通过与传统MUSIC算法比较可知，基于压缩感知的DOA估计方法具有显著 的优势(The theory of Compressive Sensing(CS)is the application of mathematics in the field of a sparse signal acquisition and reconstruction of the new theory. It breaks through the traditional limitation of Nyquist sampling theorem. It can recover certain signals or estimate their parameters far fewer samples or measurements than traditional methods. The application of compressed sensing theory to DOA estimation can solve the traditional DOA estimation in high sampling rate, as well as more of the radiation source signal conditions is difficult to position limits. This paper studies the theory of DOA estimation method based on compressed sensing theory, and simulation uses MATLAB, compared with the traditional MUSIC algorithms, DOA estimation based on compressed sensing theory method has the obvious advantage)

基于压缩感知的DOA估计方法研究_李新颖.pdf,1752399,2015-01-06