基于重采样的COLD阵列波达方向和极化参数联合估计

Joint DOA and Polarization Parameter Estimation of COLD Sensors Based on Resampling Technique

  • 摘要: 针对在低信噪比情形下DOA和极化参数估计性能严重下降的问题,提出了基于重采样的COLD阵列参数估计方法.该算法有效结合了ROOT-MUSIC和重采样技术,并对重采样技术作出了改进,利用COLD阵列ROOT-MUSIC算法,可以降低求根阶数,减少计算量;利用改进后的重采样方法,可以大幅度提升低信噪比下的参数估计性能.并通过参数估计结果可行性判定方法,保留参数估计正常值,剔除异常值.本文提出的这种算法,使在低信噪比情况下,参数估计精度得到提高.仿真实验结果验证了该算法对信号DOA和极化参数估计的有效性.

     

    Abstract: Focusing on the performance degradation of parameter estimation at low signal-to-noise ratio (SNR), a new method of direction of arrival (DOA) and polarization parameters estimation was proposed for COLD arrays in this paper. Combining the ROOT-MUSIC algorithm with a modified resampling technique, the proposed method was designed to reduce the computational complexity and improve estimation accuracy. Besides, the parameter feasibility determination method was used to preserve the correct values while removing the outliers after resampling. Results show that, the proposed algorithm can improve the accuracy of DOA and polarization parameter estimation, especially in the case of low signal-to-noise ratios. Computer simulations verify the effectiveness and demonstrate high-accuracy of the proposed DOA estimation algorithm, especially in the case of low SNR.

     

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