SAR image ship target detection method and system in passive interference scene

Abstract

The invention discloses an SAR image ship target detection method and system under a passive interference scene. The method comprises the steps: dividing an SAR image ship target detection data set under a passive interference condition into a training sample and a test sample; constructing a Faster R-CNN detection model with attention enhancement; constructing an overall loss function of a region-of-interest classification task, a region-of-interest position regression task, a target classification task, a target position regression task and a target region saliency detection task of the attention-enhanced Faster R-CNN detection model; training the attention-enhanced Faster R-CNN detection model added with the overall loss function L by using the training sample; inputting the test sample into the attention-enhanced Faster R-CNN detection model containing the weight parameters after training, predicting and outputting a target bounding box position, a target category and a confidence score of the target in the test sample, and completing SAR image ship target detection. According to the method, the SAR image ship target detection precision in the passive interference scene is improved.

Description

technical field [0001] The invention belongs to the technical field of remote sensing images, and in particular relates to a SAR image ship target detection method and system in a passive interference scene. Background technique [0002] Ship target detection in SAR images under passive interference scenarios aims at locating and identifying ship targets in SAR images under passive interference conditions. Traditional SAR image ship detection methods include template matching-based methods, knowledge-based methods and object-detection-based methods. These methods largely rely on a large number of feature engineering to detect ship targets in SAR images. However, these methods are not very adaptable to problems such as complex target backgrounds and obvious scale differences in SAR images. [0003] In recent years, deep learning-based methods have been commonly used for ship target detection in SAR images. Deep convolutional neural networks do not need to manually design fea...

AI Technical Summary

Problems solved by technology

However, since the Faster R-CNN model is mainly used in target detection tasks in natural image scenes, it does not fully consider the problem of passive interference in SAR images, resulting in poor performance of ship target detection in SAR images in passive interference scenarios. Difference

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