An Improved MUSIC Algorithm for Two Dimensional Direction Of Arrival Estimation
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摘要: 多重信号分类(MUSIC)算法是一种经典的空间谱估计算法。该文以L型阵列为例，针对2D-MUSIC算法在接收信号信噪比较小时对多个目标中方位相近的目标无法进行准确估计的问题，提出一种改进2D-MUSIC算法。该算法对经典2D-MUSIC算法所构成的协方差矩阵进行共轭重组，并将重组后矩阵的平方与原协方差矩阵的平方进行相加求平均，由此获得新的矩阵，再对该矩阵对应的噪声子空间进行加权处理，选取适当的加权系数构造新的噪声子空间，最后通过谱峰搜索识别出目标位置。计算机仿真结果表明，与2D-MUSIC算法相比，改进后的算法在接收信号信噪比较小时对多个目标中方位相近的目标也能够进行信号波达方向(DOA)估计，提高了L型阵列2维DOA估计的分辨率，具有较好的工程应用价值。
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关键词:
- 2维信号波达方向估计 /
- L型阵列 /
- 共轭重组 /
- 加权
Abstract: The MUltiple SIgnal Classification (MUSIC) algorithm is a classical spatial spectrum estimation algorithm. Taking L-shaped array as an example, an improved 2D-MUSIC algorithm is proposed for the problem that 2D-MUSIC algorithm often fails to estimate accurately targets in close proximity among multiple targets when the signal-to-noise ratio is low.The algorithm identifies the target location through spectrum peak search by first performing conjugate recombination on the covariance matrix generated by the classical 2D-MUSIC algorithm, then calculating the mean of sum of square of the recombined one and the original one as the new matrix, whose corresponding noise subspace then weighted by applying appropriate coefficients to obtain a new noise subspace. The computer simulation results show that compared with the 2D-MUSIC algorithm, the improved algorithm performs well on DOA estimation for the targets in close proximity among multiple targets when the received signal has low signal-to-noise ratio, which improves the resolution of 2D-DOA estimation with L-shaped array, with better engineering application value. -
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