The total least squares method was used in the improved algorithm to obtain the noise subspace.

改进算法利用总体最小二乘法得到噪声子空间。

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This thesis studies the feature selection method of HRRP and proposes a RATR method in target subspace based on the analysis of noise-match in HRRP space.

基于对HRRP空间雷达自动目标识别中冗余噪声匹配的分析，研究了高分辨距离像的特征选择方法，提出了一种基于目标子空间的雷达自动目标识别方法。

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The result are compared with that of eigensystem realization algorithm, which proves that the subspace method can reduce the noise influence on the parameters estimate more effectively.

通过与特征系统实现算法仿真结果比较，证明了子空间方法能更有效地降低噪声对参数估计的影响。

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