ID 原文 译文
6234 通过仿真实验和基于BioSAR 2007实测数据的半仿真实验验证。 Through simulation experiments and simulation experiment based on BioSAR 2007 half of the measured data.
6235 实验表明全极化差分SAR层析成像方法,重构结果相较于单极化,提高了高程向和形变速率精度,且有更好的鲁棒性,在信噪比为10dB时,相较于单极化差分SAR层析成像方法,能更好恢复高程向信息和形变速率。 The results show that the polarization difference SAR tomography method, reconstruction results compared with literal, raised the height to the deformation rate and precision, and has better robustness, when SNR is 10 db, compared to a unipolar differential SAR tomography method, can better restore elevation to the information and deformation rate.
6236 针对传统平行阵二维测向自由度低问题,提出一种改进型平行互素阵,基于稀疏表示方法和最小二乘法来估计目标方位。 In view of the traditional parallel array 2-d direction finding freedom low problem, proposes a modified parallel element array, based on sparse representation method and least square method to estimate the target bearing.
6237 该方法首先利用改进型互素阵构建双平行稀疏阵列,计算平行互素阵的互协方差矩阵。 This method firstly improved parallel sparse array, each element array build double parallel computing element matrix of the mutually covariance matrix.
6238 然后通过矢量化处理,利用重排,去冗余处理生成较大孔径的虚拟阵列,将二维波达方向(direction of arrival,DOA)估计问题降维为一维DOA估计问题。 By means of vector, and then a rearrangement, to deal with the redundant generates larger virtual array aperture, the 2 d DOA (direction of concatenated, DOA) dimension estimation problem for one dimensional DOA estimation problem.
6239 进一步将一维DOA估计问题转为复数信号稀疏重构问题,并利用二阶锥规划来进行求解,通过峰值搜索得到方位角信息。 A further dimensional DOA estimation problem into a complex signal sparse reconstruction problem, and by using second-order cone programming to solve, azimuth information is obtained by peak searching.
6240 最后利用方位角来构建方向矩阵,通过最小二乘方法求解俯仰角。 Finally based on the azimuth direction to construct the matrix, by least square method to solve the pitching Angle.
6241 该方法可以在没有目标先验信息的条件下,能够准确估计目标方位,且能够实现自动配对。 The method can under the condition of without a priori knowledge about the target, can accurately estimate the target bearing, and can realize automatic matching.
6242 相比传统的平行均匀线阵以及平行互素阵,该方法扩展了阵列虚拟孔径,提高了估计精度,能够辨识更多的目标源。 Compared with the traditional parallel uniform linear array and parallel element array, this method extends the virtual array aperture, improves the estimation precision, can recognize more target source.
6243 实验仿真验证了该方法的有效性。 Experimental results verify the effectiveness of the method.