CAJ | 학술논문

利用压缩感知理论解决阵列信号到达角(DOA)估计问题，具有对快拍数据量要求低、可处理相关源等优点。将压缩感知理论应用于信源DOA估计的一个关键问题是建立信源信号的稀疏化模型。该文在均匀线阵模型下系统分析了角度划分对DOA估计稀疏重构性能的影响，从对相关性的分析出发给出了信号的最优稀疏化模型。分析结果表明在实际应用中基于信源信号等正弦空间稀疏化的重构模型是最优的。实验对比了新的稀疏化模型与传统的等角度划分方式得到的流形矩阵的可重构性能，并进行了关于信号重构和信源DOA估计的详细实验分析，验证了所提模型的优越性。
이용압축감지이론해결진렬신호도체각(DOA)고계문제，구유대쾌박수거량요구저、가처리상관원등우점。장압축감지이론응용우신원DOA고계적일개관건문제시건립신원신호적희소화모형。해문재균균선진모형하계통분석료각도화분대DOA고계희소중구성능적영향，종대상관성적분석출발급출료신호적최우희소화모형。분석결과표명재실제응용중기우신원신호등정현공간희소화적중구모형시최우적。실험대비료신적희소화모형여전통적등각도화분방식득도적류형구진적가중구성능，병진행료관우신호중구화신원DOA고계적상세실험분석，험증료소제모형적우월성。
The method of Direction-Of-Arrival (DOA) estimation of array signals based on Compressive Sensing (CS) theory has advantages such as fewer snapshots requirement and the capacity of dealing with the coherent sources. Exploiting the CS theory on DOA estimation, one of the key issues is to construct the sparsity model of source signals. This paper proposes the systemic analysis about how the way of space-partition affects the performance of DOA estimation, and presents a new optimal sparse reconstruction model based on space-partition with equal sine interval through the analysis about coherence. The theoretical result shows that the reconstruction model based on the manifold matrix with equal sine interval is the best model in the practical application. Finally the experiments compare the reconstruction performance of the manifold matrix with equal sine interval with that of the manifold matrix with equal angle interval. This paper provides the experiment results about the performance of signal reconstruction and DOA estimation, respectively. The advantage of the presented sparsity model is verified.