An improved MUSIC algorithm based on singular value decomposition and subspace weighting
Under non-ideal conditions such as low signal-to-noise ratio and small number of snapshots,the classical DOA estimation algorithm seriously degrades the resolution of adjacent targets and even loses the resolu-tion.To solve this problem,an improved algorithm is proposed that combines the singular value decomposition of the reconstructed received signal covariance matrix with the improved weighted subspace method.The algorithm makes full use of cross-correlation information to construct a new received signal covariance matrix,and uses a new correction method for noise subspace information to transform the noise eigenvalues.Then the noise sub-space is weighted,and finally combined with the signal subspace weighting technology.Simulation results show that the improved algorithm can distinguish adjacent targets with an interval of 4 ° under the conditions of low sig-nal-to-noise ratio and small snapshots.Statistical analysis shows that the resolution of the proposed algorithm is significantly better than that of the classical MUSIC algorithm.
direction of arrival estimationMUSIC algorithmsingular value decompositionnoise sub-spacehigh resolution
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