A sar target identification method based on multi-feature fusion bag-of-words model

Abstract

The invention belongs to the technical field of radar target identification, and discloses a SAR target identification method based on a multi-feature fusion bag-of-words model, comprising: 1. Obtaining multiple sets of local features corresponding to each image in a training slice image and a test slice image; 2. . Obtain the visual dictionary corresponding to multiple sets of local features; 3. Encode the underlying features of multiple sets of local features to obtain the BoW model histogram features of the training slice image and the test slice image, and then obtain the fused training slice image and test slice image 4. Use the histogram intersection kernel support vector machine to identify the global features of the test slice; the invention improves the performance of identification and can be used for SAR target identification in complex scenes.

Description

technical field [0001] The invention belongs to the technical field of radar target identification, and in particular relates to a SAR target identification method based on a multi-feature fusion word bag model, which can be used to provide important information for identification, identification and classification of vehicle targets. Background technique [0002] With the continuous development of SAR imaging technology, it has become one of the indispensable remote sensing platforms for earth observation. SAR image automatic target recognition (Automatic Target Recognition, ATR), especially vehicle target recognition, is one of the important applications of SAR images, and has attracted more and more attention from researchers. A typical SAR ATR system generally includes three stages: target detection, target identification and target classification. In the three-level processing flow of SAR ATR, target identification is in the middle link, which has the function of conne...

AI Technical Summary

Problems solved by technology

Considering the difference characteristics between the local structure of the target and the clutter in the high-resolution SAR image, the traditional features only provide a rough and partial description of the target, and they cannot describe the detailed local shape and structure information of the target and the clutter, which indicates that the discrimination Cannot make full use of the rich detail information of high-resolution images

When the target and clutter have no obvious difference in texture, size and contrast, traditional features cannot show good discriminative performance

[0007] To sum up, with the continuous improvement of SAR image resolution, traditional features have great limitations for target identification in complex scenes.

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