• Title/Summary/Keyword: satellite-based model

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Test Results of WADGPS System using Satellite-based Ionospheric Delay Model for Improving Positioning Accuracy

  • So, Hyoungmin;Jang, Jaegyu;Lee, Kihoon;Song, Kiwon;Park, Junpyo
    • Journal of Positioning, Navigation, and Timing
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    • 제5권4호
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    • pp.213-219
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    • 2016
  • Most existing studies on the wide-area differential global positioning system (WADGPS) employed a grid ionosphere model for error correction in the ionospheric delay. The present study discusses the application of satellite-based ionospheric delay model that provides an error model as a plane function with regard to individual satellites in order to improve accuracy in the WADGPS. The satellite-based ionospheric delay model was developed by Stanford University in the USA. In the present study, the algorithm in the model is applied to the WADGPS system and experimental results using measurements in the Korean Peninsula are presented. Around 1 m horizontal accuracy was exhibited in the existing planar fit grid model but when the satellite-based model was applied, correction performance within 1 m was verified.

Ka-대역 위성 통신의 위한 강우에 의한 전파 감쇠 예측 모델 (Prediction Model of Rain Attenuation for Ka-Band Satellite Communication)

  • 우병훈;강희조
    • 한국정보통신학회논문지
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    • 제6권7호
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    • pp.1038-1043
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    • 2002
  • The demand for multimedia service using Ka-band satellite communication are growing rapi이y. So, in this paper, we have analyzed rain attenuation with typical model, and proposed prediction model of rain attenuation in high frequency(over 20[GHz]). Path loss model by rain attenuation is based upon rain rate of representative region(6 cities). Proposed prediction model of rain attenuation and parameter of satellite link can be available for the Ka-band satellite communication.

Line Based Transformation Model (LBTM) for high-resolution satellite imagery rectification

  • Shaker, Ahmed;Shi, Wenzhong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.225-227
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    • 2003
  • Traditional photogrammetry and satellite image rectification technique have been developed based on control-points for many decades. These techniques are driven from linked points in image space and the corresponding points in the object space in rigorous colinearity or coplanarity conditions. Recently, digital imagery facilitates the opportunity to use features as well as points for images rectification. These implementations were mainly based on rigorous models that incorporated geometric constraints into the bundle adjustment and could not be applied to the new high-resolution satellite imagery (HRSI) due to the absence of sensor calibration and satellite orbit information. This research is an attempt to establish a new Line Based Transformation Model (LBTM), which is based on linear features only or linear features with a number of ground control points instead of the traditional models that only use Ground Control Points (GCPs) for satellite imagery rectification. The new model does not require any further information about the sensor model or satellite ephemeris data. Synthetic as well as real data have been demonestrated to check the validity and fidelity of the new approach and the results showed that the LBTM can be used efficiently for rectifying HRSI.

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Performance Analysis of a Satellite-Based Ionosphere Model for WADGPS under Disturbed Ionosphere Condition

  • So, Hyoungmin;Lee, Kihoon;Kim, Kapjin;Park, Junpyo
    • Journal of Positioning, Navigation, and Timing
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    • 제8권4호
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    • pp.225-232
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    • 2019
  • The satellite-based ionospheric model consists of local first-order plane function parameters for individual satellites and provides excellent accuracy in the flat ionospheric environment of the Korean Peninsula. This paper analyzes the performance of such model under the rapid changes in the ionosphere. Rapid changes in the ionosphere were observed in Korea from September to October 2014, and a satellite-based ionosphere model was applied to Wide Area Differential GPS (WADGPS) to analyze the navigation performance and the performance of estimating ionospheric delay errors. After processing the test data, it was confirmed that there was a deterioration in navigation performance and extrapolation performance in low-latitude areas and analyzed the cause.

인공위성 패널 열해석모델 간소화 알고리즘 연구 (A STUDY ON THERMAL MODEL REDUCTION ALGORITHM FOR SATELLITE PANEL)

  • 김정훈;전형열;김승조
    • 한국전산유체공학회지
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    • 제17권4호
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    • pp.9-15
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    • 2012
  • Thermal model reduction algorithms and techniques are introduced to condense a huge satellite panel thermal model into the simplified model on the purpose of calculating the thermal responses of a satellite on orbit. Guyan condensation algorithm with the substitution matrix manipulation is developed and the mathematical procedure is depicted step by step. A block-form LU decomposition method is also invited to compare the developed algorithm. The constructed reduced thermal model induced from the detailed model based on a real satellite panel is satisfying the correlation criterion of ${\pm}2^{\circ}C$ for the validity accuracy. Guyan condensation algorithm is superior to the block-form LU decomposition method on computation time.

Bias Correction of Satellite-Based Precipitation Using Convolutional Neural Network

  • Le, Xuan-Hien;Lee, Gi Ha
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2020년도 학술발표회
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    • pp.120-120
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    • 2020
  • Spatial precipitation data is one of the essential components in modeling hydrological problems. The estimation of these data has achieved significant achievements own to the recent advances in remote sensing technology. However, there are still gaps between the satellite-derived rainfall data and observed data due to the significant dependence of rainfall on spatial and temporal characteristics. An effective approach based on the Convolutional Neural Network (CNN) model to correct the satellite-derived rainfall data is proposed in this study. The Mekong River basin, one of the largest river system in the world, was selected as a case study. The two gridded precipitation data sets with a spatial resolution of 0.25 degrees used in the CNN model are APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks). In particular, PERSIANN-CDR data is exploited as satellite-based precipitation data and APHRODITE data is considered as observed rainfall data. In addition to developing a CNN model to correct the satellite-based rain data, another statistical method based on standard deviations for precipitation bias correction was also mentioned in this study. Estimated results indicate that the CNN model illustrates better performance both in spatial and temporal correlation when compared to the standard deviation method. The finding of this study indicated that the CNN model could produce reliable estimates for the gridded precipitation bias correction problem.

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MODELING SATELLITE IMAGE STRIPS WITH COLLINEARITY-BASED AND ORBIT-BASED SENSOR MODELS

  • Kim, Hyun-Suk;Kim, Tae-Jung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.578-581
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    • 2006
  • Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

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DIRECT EPIPOLAR IMAGE GENERATION FROM IKONOS STEREO IMAGERY BASED ON RPC AND PARALLEL PROJECTION MODEL

  • Oh, Jae-Hong;Kim, Kyung-Ok
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.860-863
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    • 2006
  • Epipolar images have to be generated to stereo display aerial images or satellite images. Pushbroom sensor is used to acquire high resolution satellite images. These satellite images have curvilinear epipolar lines unlike the epipolar lines of frame images, which are straight lines. The aforementioned fact makes it difficult to generate epipolar images for pushbroom satellite images. If we assume a linear transition of the sensor having constant speed and attitude during image acquisition, we can generate epipolar images based on parallel projection model (2D Affine model). Recent high resolution images are provided with RPC values so that we can exploit these values to generate epipolar images without using ground control points and tie point. This paper provides a procedure based on the parallel projection model for generating epipolar images directly from a stereo IKONOS images, and experimental results.

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Direct Epipolar Image Generation From IKONOS Stereo Imagery Based On RPC and Parallel Projection Model

  • Oh, Jae-Hong;Shin, Sung-Woong;Kim, Kyung-Ok
    • 대한원격탐사학회지
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    • 제22권5호
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    • pp.451-456
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    • 2006
  • Epipolar images have to be generated to stereo display aerial images or satellite images. Pushbroom sensor is used to acquire high resolution satellite images. These satellite images have curvilinear epipolar lines unlike the epipolar lines of frame images, which are straight lines. The aforementioned fact makes it difficult to generate epipolar images for pushbroom satellite images. If we assume a linear transition of the sensor having constant speed and attitude during image acquisition, we can generate epipolar images based on parallel projection model (20 Affine model). Recent high resolution images are provided with RPC values so that we can exploit these values to generate epipolar images without using ground control points and tie point. This paper provides a procedure based on the parallel projection model for generating epipolar images directly from a stereo IKONOS images, and experimental results.

A Highly Secure Identity-Based Authenticated Key-Exchange Protocol for Satellite Communication

  • Yantao, Zhong;Jianfeng, Ma
    • Journal of Communications and Networks
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    • 제12권6호
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    • pp.592-599
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    • 2010
  • In recent years, significant improvements have been made to the techniques used for analyzing satellite communication and attacking satellite systems. In 2003, a research team at Los Alamos National Laboratory, USA, demonstrated the ease with which civilian global positioning system (GPS) spoofing attacks can be implemented. They fed fake signals to the GPS receiver so that it operates as though it were located at a position different from its actual location. Moreover, Galileo in-orbit validation element A and Compass-M1 civilian codes in all available frequency bands were decoded in 2007 and 2009. These events indicate that cryptography should be used in addition to the coding technique for secure and authenticated satellite communication. In this study, we address this issue by using an authenticated key-exchange protocol to build a secure and authenticated communication channel for satellite communication. Our protocol uses identity-based cryptography. We also prove the security of our protocol in the extended Canetti-Krawczyk model, which is the strongest security model for authenticated key-exchange protocols, under the random oracle assumption and computational Diffie-Hellman assumption. In addition, our protocol helps achieve high efficiency in both communication and computation and thus improve security in satellite communication.