矩阵空域预滤波目标方位估计

Matrix spatial prefiltering approach for direction-of-arrival estimation

提出了基于矩阵空域预滤波处理的目标方位估计新方法。通过设计一个空域的矩阵滤波器对传感器阵列数据进行矩阵处理,抑制阻带扇面的干扰与噪声,且尽量保证让通带扇面的信号无失真通过。由于该空域滤波器的输出仍为阵元域数据,因此可以很方便地在很多阵列信号处理算法之前通过增加空域预滤波处理来达到抑制空间干扰、提高系统处理能力的目的。文章通过目标方位估计的具体实例来说明矩阵空域预滤波处理对系统性能的改善作用。计算机仿真和实测数据处理结果表明,矩阵空域预滤波处理有效地抑制了空间干扰与噪声,提高了方位估计算法对感兴趣扇面目标的方位分辨与估计性能。此外,仿真结果表明采用分扇面空域预滤波处理方法,使基阵具有了分辨多于阵元数目信号源的能力。

An approach to direction-of-arrival （DOA） estimation for multiple narrowband farfield signals is proposed. The technique uses a novel spatial prefiltering approach. Specifically, a matrix filter is designed to spatially filter the incoming data snapshots. The unwanted components within the stopband sectors are attenuated and the desired components in the angular sector of interest pass with minimal distortion. The matrix filter spatially filters the elementspace data and generates also an element-space output, which makes it very useful by passing sensor data through a spatial prefilter prior to applying many other array processors to attenuate interferences and improve system performance. Several examples of DOA estimation problem are present to illustrate the performance of the proposed spatial prefiltering approach. Results of simulation and real data show that the prefilter can efficiently attenuate the spatial interferences and significantly improved the estimation and resolution capability of DOA estimators at low signal-to-noise ratios. In addition, the use of spatial prefilter makes it possible to estimate DOAs for multiple sources more than the number of the elements of an array.