MIMORadarDOAEstimation

  MIMO雷达模型下一种子空间谱估计方法，采用过估计的方法，以避免信源数估计的问题，直接对数据协方差矩阵进行变换，从而构造了信号子空间投影矩阵和噪声子空间投影矩阵，不需要像经典的MUSIC一样对其进行特征分解，完全避开了在一般非理想情况下MUSIC算法必须面对的识别小特征值与大特征值的麻烦，降低了复杂度，而且该方法不受快拍数的影响，在相干源情况下也能准确的估计目标的入射角，不会出现伪峰。(A subspace based DOA (Direction-Of-Arrival) estimation method for MIMO (Multiple-Input Multiple-Output) radar is studied in this paper. By transforming the data covariance matrix, we can construct the projection matrix of signal subspace and noise subspace. The computation complexity of the algorithm is reduced as it does not need to perform eigendecomposition. By using the over estimated theory, this algorithm avoid estimating the number of signal sources and can keep a good estimate performance in the case of lower SNR (Signal-to-Noise Ratios) and multi-target. )

MIMO雷达DOA估计
...............\corr_matric.m,142,2008-12-29
...............\DOAEstErr.m,2471,2009-01-06
...............\fig4-3.fig,5110,2008-12-17
...............\fig4-4.fig,4654,2008-12-17
...............\fig4-5.fig,8245,2009-01-05
...............\fig4-6-a.fig,10339,2009-01-06
...............\fig4-6-b.fig,10338,2009-01-06
...............\fig4-6-c.fig,10350,2009-01-06
...............\fig4-7.fig,7239,2009-01-04
...............\FindLocalPeak.m,723,2008-12-15
...............\MIMO_Doa_Est.m,3975,2008-12-16
...............\MSE_CRB.m,1043,2009-03-03
...............\MutTargetDoaError.m,5115,2009-03-03
...............\NewDoaEst.m,2894,2008-12-17
...............\OneTargetDoaError.m,4303,2009-01-05