Target automatic detection method and system for SAR (Synthetic Aperture Radar) image

An automatic detection and target detection technology, applied in the field of target detection based on SAR images, can solve the problem that the detection rate and false alarm rate have not reached a satisfactory level

Active Publication Date: 2021-09-10
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

However, due to the complex background of SAR images and the variety of aircraft types, there are still problems in using the EWFAN algorithm to detect aircraft, and the detection rate and false alarm rate have not reached a satisfactory level.

Method used

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  • Target automatic detection method and system for SAR (Synthetic Aperture Radar) image
  • Target automatic detection method and system for SAR (Synthetic Aperture Radar) image
  • Target automatic detection method and system for SAR (Synthetic Aperture Radar) image

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Embodiment Construction

[0048] Such as figure 1 As shown, the automatic target detection method for SAR images in this embodiment includes inputting the input image into the pre-trained feature fusion and anti-interference network FFAN (Feature Fusion and Anti-interference Network) to obtain the target frame for target detection, feature fusion and anti-interference Network FFAN includes:

[0049] The backbone network is used to downsample the input image into features of different scales, including low-level features P3, intermediate-level features P4-P6 and high-level features P7;

[0050] The pooling and channel shuffling modules are used to extract and fuse the intermediate-level features P4~P6 respectively to obtain the corresponding shuffling features P4'~P6';

[0051] The deep fusion module is used to perform deep fusion on the low-level features P3, shuffled features P4′~P6′, and high-level features P7, and respectively obtain the corresponding deep-fused low-level features P3′, shuffled fea...

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Abstract

The invention discloses an SAR image-oriented automatic target detection method and system, and the method comprises the steps: inputting an input image into a pre-trained feature fusion and anti-interference network FFAN to obtain a target frame for target detection, wherein the feature fusion and anti-interference network FFAN comprises a backbone network, a pooling and channel shuffling module, a deep fusion module, a space attention mechanism RSAM, a space feature fusion module ASFF and a classification regression network. According to the method, the features can be effectively extracted and fused, the regression precision is improved, and the detection effect is remarkably improved on the premise that the test speed is hardly influenced by the feature fusion and anti-interference network FFAN. The method has the advantage of good universality, can be used for realizing high-precision rapid detection of an airplane, and can also be used for detecting and identifying other dense targets in an SAR image.

Description

technical field [0001] The invention relates to a target detection technology based on SAR images, in particular to an automatic target detection method and system for SAR images. Background technique [0002] Target detection is a hot issue in the field of high-resolution synthetic aperture radar (SAR). Aircraft is a typical man-made target. In the military field, aircraft has important military value. Efficient and accurate acquisition of aircraft target information in airports, airspace and other locations is of great significance for real-time acquisition of battlefield military intelligence and formulation of combat plans; In the field, the detection and identification of aircraft can manage the airport more effectively. Because Synthetic Aperture Radar (SAR) has the characteristics of all-day and all-weather work, the target detection and recognition technology in SAR images has been widely concerned and researched. [0003] Traditional SAR image target detection met...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/241
Inventor 肖红光王杰岚陈立福邢进韩松涛罗汝蔡兴敏
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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