| ID | 原文 | 译文 |
| 9644 | 对于空间旋转对称进动目标,单部雷达成像仅能获得目标在雷达视线(line of sight,LOS)方向的一个切面,无法反映目标真实的三维结构,同时进动增加了成像的复杂度。 | Rotational symmetry precession for space target, single radar imaging can only obtain the radar line of sight (line of sight, LOS) in the direction of a plane, can't reflect the actual three-dimensional structure of the target, at the same time increased the complexity of the imaging precession. |
| 9645 | 利用组网雷达多视角观测的特点,提出一种基于组网雷达的旋转对称进动目标三维重构方法。 | Advantage of the characteristics of netted radar observations of multiple points of view, this paper puts forward a netted radar based rotational symmetry precession target 3 d reconstruction method. |
| 9646 | 首先建立了旋转对称进动目标的回波模型;在估计视线-轴线夹角的基础上,采用复数逆投影方法实现进动目标的二维成像,并分析了允许的夹角误差范围; | First rotational symmetry into moving target echo model is established; In estimating the line of sight - axis Angle, on the basis of the plural inverse projection method was adopted to realize precession target of 2 d imaging, and analyzes the allowed error range Angle; |
| 9647 | 基于分布式雷达二维图像,提出一种适用于旋转对称目标的三维重构方法,通过对各二维图像进行空间定标、匹配融合、强点检测和曲线圆拟合,最终实现目标的三维重构; | Based on distributed radar two-dimensional image, the paper puts forward a kind of suitable for 3 d reconstruction method of the rotational symmetry target through space in the two-dimensional image scaling, matching fusion, better detection and curve fitting, finally achieve the goal of 3 d reconstruction; |
| 9648 | 最后通过仿真实验初步验证了该方法的有效性。 | Finally, preliminary simulation results demonstrated the effectiveness of the method. |
| 9649 | 无人机利用视觉在未知区域自主着降时,提取的特征点具有数量多、随机性强等特点。 | Unmanned aerial vehicle (uav) using visual independent when the drop in unknown area, the extracted feature points has many characteristics, such as quantity, strong randomness. |
| 9650 | 针对利用随机特征点进行位姿估计精度低、稳定性差的问题,提出一种基于矢量约束的随机特征点选取算法。 | For using random feature points to pose estimation precision is low, the stability problem, put forward a kind of random feature point selection method based on vector constraints. |
| 9651 | 首先通过分析位姿估计方程可知,特征点地理坐标是影响方程组求解精度的重要因素; | First, by analyzing the pose estimation equation, the characteristic points geographic coordinates are important factors affected the accuracy of equations to solve; |
| 9652 | 然后在引入矢量角均分度、矢量模值均值及矢量模值最大值三项约束指标基础上,制定了一种基于矢量约束的特征点选取策略; | Then divide the introduction of vector Angle and the mean vector modulus value and vector modulus maximum value index based on the three constraints, developed a kind of feature point selection strategy based on vector constraints; |
| 9653 | 最后利用正交迭代算法对所选取的特征点进行位姿估计精度验证。 | Finally using orthogonal iteration algorithm for the characteristics of the selected point verifies the pose estimation precision. |