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针对DOA(Direction of Arrival)估计在低信噪比的情况下估计性能下降的问题,根据阵列协方差矩阵共轭对称的特点,采用基于Givens变换的三对角化分解方法对协方差矩阵进行三对角化,同时利用盖氏(Gerschgorin)圆递推方法准确估计信号子空间的秩,然后再对三对角矩阵进行对角化,估计出噪声子空间,利用噪声子空间与导向矢量正交实现波达方向估计,改善了低信噪比背景下估计的误差性能和稳健性。计算机仿真证明了算法的有效性。
According to the DOA (Direction of Arrival) estimation of performance degradation at low signal-to-noise ratio (SNR), according to the conjugate symmetry of the array covariance matrix, the three-diagonal decomposition method based on Givens transform is used to estimate the covariance matrix Diagonalization. At the same time, Gerschgorin circular recursion method is used to estimate the rank of signal subspace accurately. Then the diagonalization of tridiagonal matrices is performed to estimate the noise subspace, and the noise subspace is orthogonal to the steering vector Realizing the DOA estimation improves the estimated error performance and robustness in the context of low SNR. Computer simulation proves the effectiveness of the algorithm.