Multi-view three-dimensional ISAR scattering point set registration method

Abstract

The invention discloses a multi-view three-dimensional ISAR scattering point set registration method. The method comprises the steps of obtaining a source point set and a target point set of an objectbased on three-dimensional ISAR imaging; respectively performing surface fitting on each point in the source point set and each point in the target point set to extract curvature values, and selecting points of which the curvature values meet sorting requirements from a plurality of neighborhood scales as feature points of the source point set and the target point set respectively; carrying out initial registration on the source point set and the target point set: combinig a coordinate value root-mean-square error and distance root-mean-square error evaluation function to obtain an optimal matching four-point pair, and substituting the coordinates of the matching point pair into a singular value decomposition method to calculate a transformation relationship between the point sets; and obtaining a globally optimal solution by adaptively changing an iterative step length by utilizing the optimal matching four-point pair and an iterative nearest neighbor algorithm based on an adaptive threshold, so that the point set converges to the globally optimal solution. According to the method, the matching point pair with high matching degree can be effectively found, and the registration precision can be improved.

Description

technical field [0001] The invention belongs to the technical field of three-dimensional ISAR imaging, and in particular relates to a multi-view three-dimensional ISAR scattering point set registration method. Background technique [0002] 3D ISAR (Inverse Synthetic Aperture Radar) imaging can obtain the 3D ISAR scattering point set of the target. Compared with the 2D image, it can reflect the real size and shape of the target, thus providing the necessary information for the extraction of target parameters and target recognition. information support. [0003] The scattering point set obtained by 3D ISAR imaging consists of a series of scattered points containing coordinate information, which is similar to the structure of the 3D laser point cloud, but the 3D ISAR scattering point set is more sparse, and there are fewer overlapping areas between different viewing angles. Currently, for multi-view 3D ISAR Registration methods for scatter point sets are rarely available. Bas...

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Problems solved by technology

[0003]The scattering point set obtained by 3D ISAR imaging consists of a series of scattered points containing coordinate information, which is similar to the structure of the 3D laser point cloud, but the 3D ISAR scattering point set is more sparse, There are few overlapping areas between different viewing angles, and there are few registration methods for multi-view 3D ISAR scattering point sets

[0011]In summary, the algorithm for dense laser point cloud registration is relatively mature, but the 3D ISAR scattering point set is relatively sparse and there are few overlapping areas between point sets from different perspectives. The method of applying point cloud registration is more likely to generate mismatched point pairs, and it is difficult for fine registration to converge to the global optimal solution.

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