ISAR image fusion method based on target characteristics

Abstract

The invention discloses an ISAR image fusion method based on target characteristics, and relates to fusion of ISAR images. The method includes the steps that firstly, full-aperture data are segmented, and then sub-images are acquired; space characteristic points and space characteristic descriptor vectors of the sub-images are extracted, and then the space characteristic points are matched; then, the optimized space characteristic points are selected; azimuth scale variation and de-centering are conducted according to an azimuth scale factor search method; the rotation angles between the sub-images are calculated, the transformed images are rotated, and the entropy of average range images is acquired; the fusion sub-images are determined through the minimal entropy; finally, base vectors of the fusion images are acquired according to a non-negative matrix decomposition method, and then the final fusion images are determined. Complete information of targets in the fusion images is reserved, and the method can be used for fusion and real-time processing of different sub-images.

Description

technical field [0001] The invention belongs to the field of radar technology, in particular to an inverse synthetic aperture radar ISAR image fusion method, in particular to an ISAR image fusion method based on target features. Background technique [0002] Inverse Synthetic Aperture Radar (ISAR) imaging technology has been widely used in civilian and military fields including target imaging and target geometric shape identification. After the moving space target in the continuous coherent processing time undergoes translation and complex multi-directional rotation, the local scattering points and structure of the target in the ISAR image with a shorter coherent processing time will change, resulting in the loss of part of the target structure information , so it is necessary to do multiple short-term processing, and then register and fuse the short-time ISAR images, so as to obtain long-term ISAR images under multiple attitude angles. [0003] In the ISAR image fusion met...

AI Technical Summary

Problems solved by technology

However, this method has two disadvantages. One is that there are generally not many high-energy points in the usual ISAR image; the other is that the information of the fusion image obtained by this method is seriously missing.

[0005] None of the above methods can effectively extract enough feature points to accurately estimate the rotation angle. At the same time, they lack the consideration of local structure changes and azimuth scale changes of ISAR targets, and cannot perform effective image fusion on ISAR images with long coherence time.

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