基于四阶累积量虚拟阵列扩展的DOA估计

DOA Estimation of Virtual Array Extension Based on Fourth-Order Cumulant

针对Music-like方法能很好地扩展阵列孔径,但计算量较大的问题,提出了一种虚拟阵列扩展的新方法。该方法基于四阶累积量孔径扩展的性质,由实际阵元的坐标与方向矢量直接计算出虚拟阵元的坐标与方向矢量,利用两种阵元坐标之间的关系构造四阶协方差矩阵,运用MUSIC(Mu ltip le S ignal C lassification)算法对非高斯独立信号源进行DOA(D irection of Arrival)估计。该方法在任意阵列的情况下,对非高斯独立信号源进行一维与二维DOA估计,均能准确估计出多于实际阵元数目的方向角与仰角。实验表明,对一N元阵列,该方法最多能够扩展N2-N+1个虚拟阵元,能够估计出N2-N个非高斯独立信源,提高了阵列的空间分辨能力,有效抑制了高斯噪声的干扰,减少了高阶累积量协方差矩阵的计算量。

A novel method of aperture extension is presented to decrease computation cost of the Music-like method which is effective in aperture extension. Using the aperture extension property of fourth-order cumulant, this method calculates the coordinate and steer vector of virtual sensors from the coordinate and steer vector of actual sensors, uses their relation to construct the fourth-order covariance matrix, thus using MUSIC （ Multiple Signal Classification） algorithm to estimate DOA （Direction of Arrival）. This method could extend arbitrary array aperture efficiently based actual array aperture and estimate the azimuth and elevation of more non-Gaussian independent sources than the number of the actual sensors. It is shown through the simulations that using this method N^2-N ＋ 1 virtual sensors could be extended form a N-sensors array, could estimating N^2-N non-Gaussian independent sources, this method enhances the spatial resolution of the actual array, the Gaussian noise is suppress significantly and computation cost is significantly reduced.