一种改进的极化敏感阵列解相干算法
doi: 10.3724/SP.J.1146.2013.01817
An Improved Decorrelation Algorithm for Polarization Sensitive Array
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摘要: 在相干信号源情形下,常用的极化敏感阵列信号处理方法(如参数估计、波束形成等)会出现性能下降甚至失效的现象。该文在极化平滑算法的基础上提出一种改进的解相干算法,通过对各子相关矩阵选择适当的加权系数,使平滑之后的相关矩阵具有Toeplitz的形式,进而消除信号之间的相干性。该文推导了最优加权系数的表达式及最大解相干信号个数,并利用加权平滑之后的相关矩阵完成了参数估计和波束形成。计算机仿真结果表明改进的方法具有比常规极化平滑算法更优越的性能,且适用于非均匀噪声和相干噪声的情况。Abstract: The traditional polarization sensitive array signal processing methods, e.g. parameter estimation and beamformimg, can not achieve excellent performance under the situation of coherent signal sources. An improved decorrelation algorithm is proposed based on polarization smoothing algorithm. By choosing optimal weight vectors for the signal covariance matrixes of each subarray and ensuring the smoothing covariance matrix satisfies the Toeplitz constraint, the correlation between signals is then eliminated. The derivation of optimal weight vector is given and the rank of the smoothing covariance matrix is analyzed. Simulation results verify the effectiveness of the improved algorithm and the algorithm is also suitable for the nonuniform and coherent noise.
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