基于传播算子的ESPRIT极化参数估计算法

    Polarization Parameter Estimation Algorithm Based on Propagation Operator ESPRIT

    • 摘要: 针对极化敏感阵列参数估计过程中需要奇异值和特征值分解,以及低信噪比下估计误差偏大的问题,提出基于传播算子的二维旋转不变子空间(estimation of signal parameters via rotational invariance technique,ESPRIT)算法,改进算法引入非圆信号共轭相关统计信息构造一组新的接收数据,将这组新数据与真实数据重构组合求得噪声子空间;采用ESPRIT算法将信号子空间分块得到旋转不变因子,无须特征值分解和谱峰搜索,实现信号空间到达角(direction of arrival,DOA)和极化角的精确估计.所提算法在参数估计性能上要优于经典算法,在低信噪比情况下均方误差较小,并且可降低计算量,最后由Matlab仿真验证所提算法的有效性.

       

      Abstract: To solve the problem that the singular value and the eigenvalue decomposition are needed in the parameter estimation process of the polarization sensitive array, and the estimation error is too large at the low SNR, an ESPRIT algorithm was proposed in this paper based on propagation operator by using Non-circular signal conjugate related statistical information to construct a new set of received data. The new data were reconstructed and combined with the real array to obtain the noise subspace. The signal subspace were into rotation-invariant factors by using the ESPRIT algorithm, and the DOA and polarization parameters of the signal were estimated without eigenvalue decomposition and spectral peak search. Result shows that the proposed algorithm is superior to the classical algorithm in parameter estimation performance, the mean square error is small in the case of low signal to noise ratio, and it reduces the amount of calculation. Finally, the effectiveness of the proposed algorithm was verified by MATLAB simulation.

       

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