ID 原文 译文
26625 利用二维干涉式幅相估计算法的空间谱和模型阶数选择准则获得目标个数和目标方向余弦的粗估计； Using two-dimensional space spectrum of interferometric phase estimation algorithm and model selection criteria for target order number and the target direction cosine of rough estimates;
26626 使用子阵间的相位中心偏移来获得目标方向余弦的精估计； Using phase center offset between the submatrix for target direction cosine fine estimates;
26627 针对分布孔径带来的测角模糊问题，采用双尺度解模糊算法实现分布式阵列的高精度方向估计。 According to distribution of aperture Angle of fuzzy problem, fuzzy algorithm adopts double scale distributed array of high-precision direction estimation.
26628 仿真结果验证了分布式相参阵的高精度测角性能及所提算法的有效性，也验证了分布阵DOA估计中存在基线模糊门限。 Distributed parameter array is demonstrated by the simulation results of high precision Angle measuring performance and the effectiveness of the proposed algorithm, and verify the baseline fuzzy threshold that exist in the distributed array DOA estimation.
26629 现有的合成孔径雷达图像目标识别方法通常包括图像预处理、特征提取和识别算法3部分。 The existing synthetic aperture radar images target recognition methods usually include three parts image preprocessing, feature extraction and recognition algorithm.
26630 但是，预处理算法的自适应性很难得到保证。 However, it is hard to guarantee the adaptability of preprocessing algorithm.
26631 提出了一种基于主元分析和稀疏表示的目标识别算法。 Put forward a target recognition based on principal component analysis and sparse representation algorithm.
26632 首先，阐述了稀疏表示和重构的基本理论； First, this paper expounds the basic theory of sparse representation and reconstruction;
26633 其次，提出了基于主元分析和稀疏表示的合成孔径雷达图像目标识别算法； Secondly, based on principal component analysis and sparse representation of synthetic aperture radar images target recognition algorithms;
26634 最后，选取MSTAR数据库中的5类合成孔径雷达目标图像进行仿真。 Finally, select MSTAR database of five types of synthetic aperture radar target image simulation.