• The Journal of the Acoustical Society of Korea
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• v.40 no.6
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• pp.546-554
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• 2021

In the signal processing of synthetic aperture sonar, it is subject that the platform in which the sensor array is installed moves along the straight line path. In practical operation in underwater, however, the sensor platform will have trajectory disturbances, diverting from the line path. It causes phase errors in measured signals and then produces deteriorated SAS images. In this study, in order to develop towed SAS, as tools to remove the phase errors associated with the trajectory disturbances of the towfish, motion compensation technique using Redundant Phase Center (RPC) and also Phase Gradient Autofocus (PGA) method is investigated. The performances of these two approaches are examined by means of a simulation for SAS system having a sway disturbance.

• Ocean Systems Engineering
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• v.13 no.2
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• pp.195-224
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• 2023

This paper proposes a method for the acoustic imaging wherein the traditional requirement of the relative movement between the transmitter and target is overcome. This is facilitated through the beamforming acoustic array in the transmitter, in which the target is illuminated by the array at various azimuth and elevation angles without the physical movement of the acoustic array. The concept of beam steering of the acoustic array facilitates the formation of the beam at desired angular positions of azimuth and elevation angles. This paper substantiates that the combination of illumination of the target from different azimuth and elevation angles with respect to the transmitter (through the beam steering of beam forming acoustic array) and the beam steering at multiple frequencies (through SF) results in enhanced reconstruction of images of the target in the underwater scenario. This paper also demonstrates the possibility of reconstruction of the image of a target in underwater without invoking the traditional algorithms of Digital Image Processing (DIP). This paper comprehensively and succinctly presents all the empirical formulae required for modelling the acoustic medium and the target to facilitate the reader with a comprehensive summary document incorporating the various parameters of multi-disciplinary nature.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.222-229
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• 2016

Active synthetic aperture sonar on the small UUV is generated several trajectory disturbances under the influences of underwater environments, and causing a large error in the synthetic aperture processing. In this paper, we analyzed the effects of azimuth resolution for the phase mismatch of the synthetic aperture focus processing when the periodic or random trajectory disturbances was generated on the side direction. The simulation results show that ghost targets are generated and azimuth resolution is very deteriorated when disturbance amplitude is greater than $0.3{\lambda}$ and disturbance period is greater than $2L_{sa}$ in the periodic trajectory disturbances environments. And detection performance on the seabed small objects by the synthetic aperture processing is shown that there is a significant effects on the azimuth resolution depending on the types and conditions of the platform trajectory disturbance variations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.49-60
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• 2012

Synthetic aperture radar (SAR) has been employed in various fields due to its capability to generate high resolution images regardless of weather and visibility. This paper presents a performance analysis on the image formation of high resolution SAR according to various slant range distance and synthetic aperture lengths using a range migration algorithm simulator. Although the visual performance on the SAR image is more accurate, a numeric analysis resulted in a comparable measurement. More specifically, raw data were generated for an ideal point target upon imaging geometries and design parameters such as slant range distance and synthetic aperture lengths. Finally, spatial resolution, peak to sidelobe ratio and integrated sidelobe ratio are drawn to provide SAR capabilities in the initial concept design, final in-flight calibration and validation stages.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.501-504
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• 2000

The classical image reconstruction for stripmap SAR is the range-Doppler imaging. However, when the spotlight SAR system was envisioned, range-Bowler imaging fumed out to fail rapidly in this SAR imaging modality. What is referred to as polar format processing, which is based on the plane wave approximation, was introduced for imaging from spotlight SAR data. This paper has been studied for the raw data processing schemes in the spotlight-mode synthetic aperture radar. we apply the wavefront reconstruction scheme that does not utilize the approximation in spotlight-mode SAR imaging modelity, and compare the performance of target imaging with the polar format inversion scheme.

• Proceedings of the KSRS Conference
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• v.2
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• pp.964-968
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• 2006

Bora events over the Adriatic Sea and Black Sea are investigated by using synthetic aperture radar (SAR) images acquired by the Advanced Synthetic Aperture Radar (ASAR) onboard the European Envisat satellite. These images show pronounced elongated patterns of increased sea surface roughness caused by bora winds. The comparison of the SAR images with wind fields derived from Quikscat data confirms that in all cases a strong northeasterly wind was blowing from the mountains onto the sea. It is shown that the SAR images reveal details of the spatial extent of the bora wind fields over the sea which cannot be obtained by other instruments. Furtheremore, also quantitative information on the wind field is extracted from the SAR images by using a wind scatterometer model.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.66-69
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• 2017

본 논문에서는 깊은 합성 곱 신경망 (Deep Convolutional Neural Network) 를 이용해서 SAR (Synthetic Aperture Radar) 영상의 반전 잡음 (speckle noise) 성분을 제거하는 기법을 제안하고자 한다. Deep Convolutional Neural Network는 이미지의 데이터 특성에 적합한 딥 러닝 방법이고, 이는 SAR 위성영상의 반전 잡음 제거에 사용해도 효과적이다. 반전 잡음 필터 모델 추정을 위한 학습은 임의로 반전 잡음을 합성한 트레이닝 이미지들과 원본 트레이닝 이미지들을 이용한 회귀모델을 통해 진행된다. 학습을 통해 얻은 반전 잡음 필터는 기존 알고리즘에 비해 우수한 외곽선 보존 성능을 나타냄을 확인하였다.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.219-220
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• 1998

Although a single-element synthetic aperture system can produce high-resolution beam profile, it is not a highly practical system because of its low signal to noise ratio against conventional system's. A multi-element synthetic aperture processing has been proposed with defocusing in this paper. A multi element subaperture defocused to emulate a single element spatial response with high acoustic power. The results have higher signal to noise and better contrast resolution than conventional synthetic aperture method.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1349-1351
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• 2003

In this paper, theoretical channels model of Synthetic Aperture Radiometer is presented. Based on this model, how amplitude imbalance, phase imbalance and mutual coupling between the different channels effect brightness temperature image retrieving is analyzed. The computer simulation results are also presented to find out the cause of the along-track streaks usually appeared in the retrieved brightness temperature image. In addition, a new system calibration approach is introduced to solve this problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1858-1872
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• 2023

With the advance of radar technologies, the availability of synthetic aperture radar (SAR) images increases. To improve application of SAR images, a management system for SAR images is proposed in this paper. The system provides trainable land cover classification module and display of SAR images on the map. Users of the system can create their own classifier with their data, and obtain the classified results of newly captured SAR images by applying the classifier to the images. The classifier is based on convolutional neural network structure. Since there are differences among SAR images depending on capturing method and devices, a fixed classifier cannot cover all types of SAR land cover classification problems. Thus, it is adopted to create each user's classifier. In our experiments, it is shown that the module works well with two different SAR datasets. With this system, SAR data and land cover classification results are managed and easily displayed.