基于特征配准的ISAR图像方位定标方法

发布时间：2018-04-09 14:32

本文选题：逆合成孔径雷达　切入点：尺度不变特征变换　出处：《电子与信息学报》2014年09期

【摘要】：逆合成孔径雷达(ISAR)成像利用目标相对雷达视线的姿态变化形成的合成孔径获得方位高分辨,成像方位为多普勒轴,通常需要估计目标的有效转动速度以实现ISAR图像的方位定标从而体现目标真实尺寸。现有算法通常利用信号的运动参数估计和图像整体配准。该文提出利用子孔径ISAR图像的特征提取和配对,根据特征点坐标估计目标的有效转角速度。首先利用尺度不变特征变换(SIFT)和快速鲁棒特征(SURF)对两幅ISAR图像进行特征点提取;然后分别采用最短欧氏距离和随机采样一致性(RANSAC)进行特征点的匹配和失配点的剔除;最后根据配对特征点的坐标和能量估算有效转角速度,实现ISAR图像方位定标。仿真数据和实测数据验证了该算法的精确性和稳健性。
[Abstract]:Inverse synthetic Aperture Radar (ISAR) imaging obtains high azimuth resolution by using the synthetic aperture formed by the change of the target's attitude relative to the radar line of sight. The imaging azimuth is a Doppler axis.It is usually necessary to estimate the effective rotation velocity of the target to realize the azimuth calibration of the ISAR image to reflect the real size of the target.The existing algorithms usually use signal motion parameter estimation and image registration.In this paper, the feature extraction and matching of subaperture ISAR images are used to estimate the effective angular velocity of the target according to the coordinates of the feature points.Firstly, two ISAR images are extracted by scale invariant feature transform (sift) and fast robust feature map (surf), and then the shortest Euclidean distance and random sampling consistency are used to match the feature points and eliminate the mismatch points.Finally, the effective angular velocity is estimated according to the coordinate and energy of the matching feature points, and the azimuth calibration of ISAR image is realized.The accuracy and robustness of the algorithm are verified by simulation data and measured data.
【作者单位】：西安电子科技大学雷达信号处理国家重点实验室;
【基金】：国家自然科学基金(61301280,61222108)资助课题
【分类号】：TN957.52

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