Flutter detection correction method based on RFM model bundle adjustment and image resampling

Abstract

The invention relates to a flutter detection correction method based on RFM model bundle adjustment and image resampling. The method comprises two parts: generating virtual control points based on theoriginal RPC of a three-line array image, obtaining dense matching points through employing multi-view image constraint matching, adding the virtual control points and the dense matching points intoa block adjustment model, calculating the back projection residual error of the dense matching points of the three-line array image after adjustment, and carrying out flutter detection analysis; meanwhile, based on the flutter detection result, resampling the image to generate a distortionless image, smoothing the attitude data to regenerate a high-precision RPC, and therefore synchronous reconstruction of the imaging model and the image is realized. Compared with the prior art, the method has the advantages of realizing synchronous correction of the imaging model and the image, effectively eliminating flutter influence and the like.

Description

technical field [0001] The invention relates to the technical field of satellite platform flutter detection and correction, in particular to a flutter detection and correction method based on RFM model beam adjustment and image resampling. Background technique [0002] In recent years, high-resolution remote sensing earth observation technology has developed rapidly, and has been widely used in land and resource exploration, establishment and update of national basic geographic information database and other fields. However, when high-resolution remote sensing satellites are in orbit, attitude jitter often occurs, which causes satellite attitude instability and time-related relative attitude errors, thereby affecting the satellite geometric positioning accuracy and the quality of satellite image products. [0003] At present, many scholars study the attitude flutter detection methods of in-orbit satellites, and they are often divided into three categories according to the de...

AI Technical Summary

Problems solved by technology

[0008] Existing technologies have done a lot of work on chatter detection based on multi-spectral image parallax structure and stereo image projection deviation or dense control points. Although the influence of chatter has been eliminated and the positioning accuracy has been improved, the imaging model and image The synchronous correction of the imaging model and the image respectively is inefficient.

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