Synthetic aperture radar target identification method based on auxiliary decision update learning

A technology of synthetic aperture radar and target recognition, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of difficult feature extraction of SAR images, inability to intuitively understand SAR images, and inability to adapt to real-time requirements, etc. , to achieve the effect of improving recognition efficiency and avoiding repeated training

Active Publication Date: 2018-04-06
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

However, these studies are based on optical image data
However, the imaging mechanism of SAR images is very different from that of ordinary optical sensors, resulting in that SAR images cannot be intuitively understood like optical images. The newly added SAR images do not have classification labels, and it must be trained to confirm

Method used

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  • Synthetic aperture radar target identification method based on auxiliary decision update learning
  • Synthetic aperture radar target identification method based on auxiliary decision update learning
  • Synthetic aperture radar target identification method based on auxiliary decision update learning

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Embodiment

[0045] The embodiment of the present invention adopts MSTAR image data, and now MSTAR is briefly introduced.

[0046]The MSTAR (Moving and Stationary Target Acquisition Recognition) project was launched in 1994 as a joint research project provided by the Defense Advanced Research Project Agency (DARPA) and the Air Force Research Laboratory (AFRL). A SARATR subject. The experimental data adopts the spotlight MSTAR SAR image set of ground military vehicles, the image resolution is 0.3m×0.3m, and the pixel size is 128×128. Now MSTAR data has become a standard database for evaluating SAR target recognition and classification algorithms. Most of the SAR target recognition and classification algorithms published in authoritative journals and conferences use MSTAR data for testing and evaluation.

[0047] attached image 3 The size of the MSTAR image is 128×128, and the image contains 3 regions: tank, shadow and background.

[0048] The purpose of the invention is to enable the S...

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Abstract

The invention belongs to the radar remote sensing application technology field and particularly relates to a synthetic aperture radar target identification method based on auxiliary decision update learning. According to the method, a small amount of initial training samples are utilized to train an initial model, newly-added unlabeled images are utilized as test samples, the identification results are taken as training samples for next training, on the basis of the existing model, iterative training is carried out till an identification system with stable and mature identification efficiencyis acquired. The method is advantaged in that the convolutional neural network is utilized as the main body to extract deep characteristics of SAR targets to carry out classification, in combination with auxiliary decision of an auxiliary classifier, so the newly-added unlabeled SAR images can be directly applied to the existing classifier, moreover, repeated sample training is avoided, and identification efficiency is improved.

Description

[0001] technical field [0002] The invention belongs to the technical field of radar remote sensing applications, and in particular relates to a synthetic aperture radar target recognition method based on auxiliary decision update learning. Background technique [0003] Synthetic Aperture Radar (hereinafter referred to as SAR) has the characteristics of all-time and all-weather, and is an important means of earth observation. SAR target recognition uses SAR image information to realize the determination of target types, models and other attributes. It has clear application requirements in military fields such as battlefield reconnaissance and precision strikes. It is one of the key technologies to improve the information perception ability of SAR sensors and realize the application of SAR technology. [0004] SAR target recognition performance is closely related to training samples. Target recognition requires a large number of samples with classification labels, which requi...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F18/24G06F18/214
Inventor 崔宗勇唐翠曹宗杰
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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