In this paper, an automatic target recognition (ATR) system based on synthetic aperture radar (SAR) is proposed. This
ATR system can play an important role in the simulation of up-to-data battlefield environment and be used in ATR
research. To establish an integral and available system, the processing of SAR image was divided into four main stages
which are de-noise, detection, cluster-discrimination and segment-recognition, respectively. The first three stages are
used for searching region of interest (ROI). Once the ROIs are extracted, the recognition stage will be taken to compute
the similarity between the ROIs and the templates in the electromagnetic simulation software National Electromagnetic
Scattering Code (NESC). Due to the lack of the SAR raw data, the electromagnetic simulated images are added to the
measured SAR background to simulate the battlefield environment8. The purpose of the system is to find the ROIs which
can be the artificial military targets such as tanks, armored cars and so on and to categorize the ROIs into the right
classes according to the existing templates. From the results we can see that the proposed system achieves a satisfactory result.
Target detection is an important part of an automatic target recognition (ATR) system. There would be many false
alarms if using constant false alarm rate (CFAR) algorithm directly on complex synthetic aperture radar (SAR) images
with tremendous speckle. Usually, the speckle should be reduced previously before CFAR. In this paper, a wavelet
transform de-noise and an improved CFAR algorithm have been combined to detect military targets from SAR image.
Different threshold methods were used in the wavelet domain when dealing with the detail information and non-detail
information in the image to receive the edge information and reduce the speckle. Then a three-stage CFAR algorithm
was used to detect the de-noised image. This algorithm contains global CFAR, local CFAR and count filters. Good
results are obtained when the method is used to process high-resolution, HH polarization SAR images. Such algorithms
could be arranged in the SAR image based automatic target recognition system.
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