CAJ | 학술논문

针对相干源方位估计问题，本文在PVFS（Particle Velocity Field Smoothing）算法的基础上，提出一种新的算法。该算法通过对PVFS算法构造出的协方差矩阵进行特征值分解，利用得到的特征值及特征向量构造新的噪声子空间，然后运用子空间原理实现相干源的方位估计。该算法无需已知相干源的信源数目且不会损失阵列孔径，具有较好的相干源方位估计性能，计算机仿真结果验证了本文算法的有效性。
침대상간원방위고계문제，본문재PVFS（Particle Velocity Field Smoothing）산법적기출상，제출일충신적산법。해산법통과대PVFS산법구조출적협방차구진진행특정치분해，이용득도적특정치급특정향량구조신적조성자공간，연후운용자공간원리실현상간원적방위고계。해산법무수이지상간원적신원수목차불회손실진렬공경，구유교호적상간원방위고계성능，계산궤방진결과험증료본문산법적유효성。
Aiming at the problem of DOA estimation of coherent sources, this paper proposes a new algorithm based on PVFS algorithm. Through the eigenvalue decomposition of the covariance matrix conformed by PVFS al-gorithm and using eigenvalues and the corresponding eigenvectors to construct new noise subspace, this paper real-izes DOA estimation of coherent sources by subspace theory. The algorithm has good DOA estimation perfor-mance for coherent sources without knowing number of coherent sources and losing array aperture. The results of computer simulation verify the validity of the algorithm.