摘要
针对现有的很多波达方向估计算法涉及到数据协方差矩阵的估计及其特征分解,甚至是求逆,导致运算复杂度高的问题,提出了基于快速傅里叶变换的子孔径MUSIC波达方向估计算法。首先将等距线阵的接收数据矢量均匀划分为4个子矢量,然后对各个子矢量分别求FFT。将FFT的结果相干积累,并找到最大峰值点。最后,利用子矢量FFT的结果中与最大峰值点对应的数据构造新的降维矢量,借助MUSIC算法进行波达方向估计。该方法避免了直接接收数据的协方差矩阵估计和特征分解,有效地降低了运算量和计算复杂度,在阵元数和快拍数都较多的情况下优越性尤为明显。计算机仿真验证了所提方法的有效性和优越性。
The most available direction of arrival（DOA）estimation algorithms require covariance matrix estimation and eigendecomposition,or even its inversion,thus increasing the computational complexity.Here a novel sub-aperture multiple sigal classification（MUSIC）algorithm for DOA estimation based on fast Fourier transform（FFT）is proposed.Firstly,each received data vector of uniform linear array（ULA）is portioned into four sub-vectors.Then FFT is applied to each sub-vector to achieve the coherent integration.By utilizing the data corresponding to the peaks of coherent integration in each sub-vector,a reduced-dimensional data vector is constructed for DOA estimation in terms of MUSIC.Since the full-dimensional covariance matrix estimation and eigendecomposition are avoided,the computational complexity is relatively low.Numerical examples are provided to verify the effectiveness and superiority of the proposed method.
出处
《数据采集与处理》
CSCD
北大核心
2015年第4期875-880,共6页
Journal of Data Acquisition and Processing
基金
浙江省自然科学基金青年基金(LQ12F01002)资助项目
关键词
子孔径MUSIC
快速傅里叶变换
波达方向
等距线阵
sub-aperture MUSIC
fast Fourier transform（FFT）
direction of arrival（DOA）
uniform linear array（ULA）
