• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.462-475
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• 2022

Different from the field of electro-optical(EO) image analysis, there has been less interest in similarity metrics between synthetic aperture radar(SAR) target images. A reliable and objective similarity analysis for SAR target images is expected to enable the verification of the SAR measurement process or provide the guidelines of target CAD modeling that can be used for simulating realistic SAR target images. For this purpose, this paper presents a similarity analysis method based on the siamese network that quantifies the subjective assessment through the distance learning of similar and dissimilar SAR target image pairs. The proposed method is applied to MSTAR SAR target images of slightly different depression angles and the resultant metrics are compared and analyzed with qualitative evaluation. Since the image similarity is somewhat related to recognition performance, the capacity of the proposed method for target recognition is further checked experimentally with the confusion matrix.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.355-365
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• 2000

The interferometric correlation, or coherence, is calculated to measure the variance of the interferometric phase and amplitude within the neighbourhood of any location within the image at a result of SAR (Synthetic Aperture Radar) interferometric process which utilizes the phase information of the images. The coherence contains additional information that is useful for detecting point targets which change their location in an area of interest (AOI). In this research, a RGB colour composite image was generated with a intensity image (master image), a intensity change image as a difference between master image and slave image, and a coherence image generated as a part of SAR interferometric processing. We developed a technique performing detection of a point target movement using SAR interferometry and applied it to suitable tandem pair images of ERS-1 and ERS-2 as test data. The possibility of change detection of a point target in the AOI could be identified with the technique proposed in this research.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.188-194
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• 2010

In this paper, the typical Synthetic Aperture Radar (SAR) image quality parameters and analysis method are defined, and the SAR image analysis tool is presented for SAR image evaluation. The structure of the developed SAR image analysis tool consists of four key modules; point target analysis (PTA) module, distributed target analysis (DTA) module, ambiguity analysis (AMA) module, and NESZ analysis (NESZA) module. The developed tool is able to extract the various SAR system parameters from standard SAR product format files. Based on these extracted system parameters, typical SAR image quality parameters are derived from SAR image data.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.12-21
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• 2021

For successful automatic target recognition(ATR) with synthetic aperture radar(SAR) imagery, SAR target images of the database should have the identical or highly similar resolution with those collected from SAR sensors. However, it is time-consuming or infeasible to construct the multiple databases with different resolutions depending on the operating SAR system. In this paper, an approach for resolution conversion of SAR target images is proposed based on conditional generative adversarial network(cGAN). First, a number of pairs consisting of SAR target images with two different resolutions are obtained via SAR simulation and then used to train the cGAN model. Finally, the model generates the SAR target image whose resolution is converted from the original one. The similarity analysis is performed to validate reliability of the generated images. The cGAN model is further applied to measured MSTAR SAR target images in order to estimate its potential for real application.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.1
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• pp.51-57
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• 2020

The fighter pilot uses radar mounted on the fighter to obtain high-resolution SAR (Synthetic Aperture Radar) images for a specific area of distance, and then the pilot visually classifies targets within the image. However, the target configuration captured in the SAR image is relatively small in size, and distortion of that type occurs depending on the depression angle, making it difficult for pilot to classify the type of target. Also, being present with various types of clutters, there should be errors in target classification and pilots should be even worse if tasks such as navigation and situational awareness are carried out simultaneously. In this paper, the concept of operation and functional structure of radar system for fighter jets were presented to transfer the SAR image target classification task of fighter pilots to radar system, and the method of target classification with high accuracy was studied using the CNN ensemble model to archive higher classification accuracy than single CNN model.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.4
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• pp.275-281
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• 2019

A synthetic aperture radar(SAR) satellite is more effective than an optical satellite for target analysis because an SAR satellite can provide two-dimensional electromagnetic scattering distribution of a target during all-weather and day-and-night operations. To conduct target analysis while considering the earth observation interval of an SAR satellite, observing a specific area as wide as possible would be advantageous. However, wider the observation area, worse is the resolution of the associated SAR satellite image. Although conventional methods for improving the resolution of radar images can be employed for addressing this issue, few studies have been conducted for improving the resolution of SAR satellite images and analyzing the performance. Hence, in this study, the applicability of conventional methods to SAR satellite images is investigated. SAR target detection was first applied to Korea Multipurpose Satellite-5(KOMPSAT-5) SAR images provided by Korea Aerospace Research Institute for extracting target responses. Extrapolation, RELAX, and MUSIC algorithms were subsequently applied to the target responses for improving the resolution, and the corresponding performance was thereby analyzed.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.443-461
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• 2022

Target Detection in synthetic aperture radar(SAR) image is critical for military and national defense. In this paper, we propose YOLOv4-Attention architecture which adds attention modules to YOLOv4 backbone architecture to complement the feature extraction ability for SAR target detection with high accuracy. For training and testing our framework, we present new SAR embedding datasets based on MSTAR SAR public datasets which are about poor environments for target detection such as various clutter, crowded objects, various object size, close to buildings, and weakness of signal-to-clutter ratio. Experiments show that our Attention YOLOv4 architecture outperforms original YOLOv4 architecture in SAR image target detection tasks in poor environments for target detection.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.254-257
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• 2007

This paper presents an examination of the spatial integration method for extracting the RCS of a trihedral corner reflector from SAR images for SAR external calibration. An exact external radiometric calibration technique is required for extracting an exact calibration constant. Therefore, we examine the accuracy of the spatial integration method, which is commonly used for the SAR external radiometric calibration. At first, an SAR image for a trihedral corner reflector is simulated with a high-resolution SAR impulse response with a known theoretical RCS of the reflector, and a background clutter image for the high resolution SAR system is also generated. Then, a SAR image in a high resolution is generated for a trihedral comer reflector located on a background clutter by superposition of the two SAR images. The radar cross section of a trihedral corner reflector in the SAR image is retrieved by integrating the radar signals of the pixels adjacent to the reflector for various size of the integration area. By comparison of the measured RCS by the integration method and the theoretical RCS of the reflector, the effect of the size of the integration area on the extraction of the calibration constant is examined.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.297-304
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• 2010

Since the change in Doppler centroid according to moving targets brings alteration to the phase in azimuth differential signals of synthetic aperture radar (SAR) data, one can measure the velocity of the moving targets using this effect. In this study, we will investigate theoretically measuring the velocity of an object from azimuth differential signals by using range compressed data which is the interim outcome of treatment from the simulated SAR raw data of moving targets on the background of sea clutter. Also, it will provide evaluation for the elements that affect the estimation error of velocity from a single SAR sensor. By making RADARSAT-1 simulated image as a specific case, the research includes comparisons for the means of velocity measurement classified by the directions of movement in the four following cases. 1. A case of a single target without currents, 2. A case of a single target with tidal currents of 0.5 m/s, 1 m/s, and 3 m/s, 3. A case of two targets on a same azimuth line moving in a same direction and velocity, 4. A case of a single target contiguous to land where radar backscatter is strong. As a result, when two moving targets exist in SAR image outside the range of approximately 256 pixels, the velocity of the object can be measured with high accuracy. However, when other moving targets exist in the range of approximately 128 pixels or when the target was contiguous to the land of strong backscatter coefficient (NRCS: normalized radar cross section), the estimated velocity was in error by 10% at the maximum. This is because in the process of assuming the target's location, an error occurs due to the differential signals affected by other scatterers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.183-194
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• 2011

Synthetic aperture radar (SAR) is widely used because of high resolution imaging capability in all weather and day/night condition. In this paper development of Spotlight SAR simulator is proposed for image quality analysis. Proposed SAR simulator is based on the SAR system design parameters so that SAR image performance can be expected which is essential throughout the full system development procedure from the initial concept design stage to the final in-flight calibration and validation stage. The raw data of ideal point target is first generated by taking account of the flight and imaging geometry and the various SAR system design parameters, and the Spotlight image formation algorithm is implemented in order to obtain the point target response. Finally the image quality of the generated raw data is analyzed in terms of spatial resolution, peak to sidelobe ratio and integrated sidelobe ratio.