摘要
最小方差无失真响应(MVDR)算法是一种经典的波束形成算法,同时也能实现DOA估计,但是其分辨力往往比较低。针对这一不足,提出了一种改进的MVDR相干信源DOA估计算法。该算法首先对阵列接收数据阵进行共轭重排构造出增广数据矩阵,然后利用奇异值分解(SVD)求出增广矩阵的伪逆,再用传统的MVDR算法进行DOA估计。仿真结果表明,与传统的MVDR算法和前后向空间平滑算法相比,在阵元数较少和快拍数较低的情况下,该算法具有更高的DOA估计精度和分辨力,因而是一种很好的相干信号DOA估计算法。
MVDR（minimum variance distortion response）algorithm is a classical beamforming algotithm in array signal processing,and it also can be used for DOA estimating,but there has usually a low resolution.In order to resolve this shortage,an improved algorithm is proposed.An augmentation matrix is constructed firstly by this algorithm via rearranging its receiving data matrix,then SVD（singular value decomposition） is used to solve augmentation matrix inversion and the traditional MVDR algorithm is used to estimate DOA lastly.Compared with the traditional MVDR algorithm and forward and backward spatial smoothing algorithm,the simulation results indicate in the fewer elements and lower snapshots conditions,this improved algorithm has a higher estimating accuracy and resolution,so it is also a good algorithm of coherent signals DOA estimation.
出处
《电子信息对抗技术》
2012年第6期6-10,42,共6页
Electronic Information Warfare Technology
关键词
DOA估计
MVDR
相干信源
奇异值分解
DOA estimation
MVDR
coherent signals
singular value decomposition（SVD）
