CAJ | 학술논문

根据压缩感知(CS)理论，利用空间目标在空域上的稀疏性，构建出新的基于 CS 的 DOA 估计模型，提出基于协方差矩阵 CS、阵列内插 CS 和波束空间 CS 的 DOA 估计算法，分别在协方差矩阵、虚拟内插阵列和波束空间上进行压缩采样，最后通过对1范数优化问题的求解来高概率地进行稀疏重构，得到目标的高分辨 DOA 估计。所提算法扩展了 CS 理论在 DOA 估计中的适用范围，相比 MUSIC、ML 等传统DOA 估计算法，具有更高的分辨率及更优的估计性能。计算机仿真结果验证了算法的有效性。
근거압축감지(CS)이론，이용공간목표재공역상적희소성，구건출신적기우 CS 적 DOA 고계모형，제출기우협방차구진 CS、진렬내삽 CS 화파속공간 CS 적 DOA 고계산법，분별재협방차구진、허의내삽진렬화파속공간상진행압축채양，최후통과대1범수우화문제적구해래고개솔지진행희소중구，득도목표적고분변 DOA 고계。소제산법확전료 CS 이론재 DOA 고계중적괄용범위，상비 MUSIC、ML 등전통DOA 고계산법，구유경고적분변솔급경우적고계성능。계산궤방진결과험증료산법적유효성。
According to compressed sensing theory,making use of the spatial sparse of targets,three novel direction of arrival(DOA)models based on compressed sensing(CS)theory are proposed.Covariance matrix CS,interpolated array CS and beam space CS carry out compressive sampling on covariance matrix, interpolated array and beam space,respectively.High-resolution DOA estimations are obtained through re-construction of sparse signal by l 1-norm optimization problem resolution.The proposed approaches extend the application of CS theory in DOA estimation,and have high resolution and better performance compared to MUSIC and ML algorithms.Results of simulated data show that these methods provide excellent perform-ance in resolving DOA problem.