ID 原文 译文
19275 限于无人机(UAV)的载重与尺寸，接收阵列通常较小，解多普勒模糊的空域波束形成能力不足。 Due to the weight and size ofUnmanned Aerial Vehicle (UAV), the receiving array is usually small, and the ability of spatial beam-formingfor Doppler ambiguity resolution is insufficient.
19276 此外，前视SAR回波方位多普勒梯度小、带宽窄，使得接收带宽未被充分利用。 In addition, the small Doppler gradient and narrow bandwidth of forward-looking SAR echo make the receiving bandwidth underutilized.
19277 基于以上问题，该文提出多普勒分集前视SAR成像方法。 Based on the above problems, aDoppler diversity Multiple Input Multiple Output (MIMO) forward-looking SAR imaging method is proposed.
19278 该算法在前视SAR成像技术的基础上，利用多普勒分集MIMO技术，将多普勒窄带前视回波调制于不同多普勒中心以达到充分利用多普勒接收带宽的目的。 Based on the forward-looking SAR imaging technology, the narrow-band forward-looking Doppler echo is modulated to different Doppler centers by using Doppler diversity MIMO technology to make full use of the Doppler receiving bandwidth.
19279 进而，可获得一个数倍于真实接收阵列孔径的虚拟接收阵列，极大地扩展了接收通道，有效地改善了前视SAR成像解多普勒左右模糊的性能。 Furthermore, a virtual receiving array with several times the aperture of the real receiving array can be obtained, which expands greatly the receiving channel and improves effectively the performance of forward-looking SAR imaging in de-Doppler left-right ambiguity.
19280 惩罚优化问题常常用于在有噪声的条件下用较少的观测个数来求解线性逆问题。 Penalized programs are widely used to solve linear inverse problems in the presence of noise.
19281 目前，对惩罚优化问题恢复误差的研究主要存在以下两点不足：一是对权重参数往往有要求；二是噪声的方向对误差的影响未知。 For now, the study of the performance of panelized programs has two disadvantages. First, the results have some limitations on the tradeoff parameters. Second, the effect of the direction of the noise is not clear.
19282 针对这两个问题，该文研究了当存在有界噪声时，惩罚优化问题恢复的误差界。 This paper studies the performance of penalized programs when bounded noise is presented.
19283 首先，该文从问题的几何出发，给定了一个几何条件。 A geometry condition which is used to study the noise-free problems and constrained problems is provided.
19284 当这一条件满足时，就能够推导出惩罚优化问题恢复的一个明确的误差界。这个误差界保证了恢复的解是稳定的，也就是说，恢复误差不会超过观测误差的常数倍。 Under this condition, an explicit error bound which guarantees stable recovery (i.e., the recovery error is bounded by the observation noise up to some constant factor) is proposed.