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无误差阵列协方差矩阵分离的阵列自校正方法

Array self-calibration method based on covariance matrix separation of error-free array

  • 摘要: 针对高分辨方位估计方法受阵列幅度相位影响导致性能退化的问题, 提出一种无误差阵列协方差矩阵分离的阵列自校正方法。该方法利用协方差矩阵重构方法获取近似无误差阵列的协方差矩阵, 以弱化协方差矩阵中的阵列误差, 并利用特征结构配置方法求解幅度和相位误差。迭代上述重构方法和特征结构配置方法, 实现从未校正阵列的协方差矩阵中分离出无误差阵列的协方差矩阵和幅度相位误差矩阵。仿真结果表明, 该方法准确地估计阵列误差, 利用重构协方差矩阵进行方位估计能够提高方位估计精度和分辨力。湖试试验结果表明, 经阵列校正后, 空间中方位角度邻近的声源和干扰目标可被分辨。

     

    Abstract: Because the array amplitude and phase errors will degrade the performance of the high-resolution direction of arrival (DOA) estimation method, an array self-calibration method based on the covariance matrix separation of the error-free array is proposed. This method applies the covariance matrix reconstruction method to obtain the covariance matrix of an approximate error-free array, which weakens the array error in the covariance matrix. Then, the eigenstructure method is used to solve the amplitude and phase errors. The above reconstruction method and eigenstructure method are iterated to separate the error-free array covariance matrix and the amplitude-phase error matrix from the covariance matrix of the uncalibrated array. Simulation results show that the proposed method can accurately estimate the array errors, and using the reconstructed covariance matrix for DOA estimation can improve the resolution and estimation accuracy. The lake experiment results show that the sound source and interference target with adjacent azimuth angles can be distinguished after calibrating the array using the proposed method.

     

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