• 대한원격탐사학회지
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• 제22권5호
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• pp.367-372
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• 2006

Cloud detection algorithm is being developed as primary one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-IR and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithms and preliminary test results of both algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.980-998
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• 2023

In Low Earth Orbit (LEO) satellite networks, satellites operate fast and the inter-satellite link change period is short. In order to sense the spectrum state in LEO satellite networks in real-time, a space-based satellite network intelligent spectrum sensing algorithm based on artificial neural network (ANN) is proposed, while Geosynchronous Earth Orbit (GEO) satellites are introduced to make fast and effective judgments on the spectrum state of LEO satellites by using their stronger arithmetic power. Firstly, the visibility constraints between LEO satellites and GEO satellites are analyzed to derive the inter-satellite link building matrix and complete the inter-satellite link situational awareness. Secondly, an ANN-based energy detection (ANN-ED) algorithm is proposed based on the traditional energy detection algorithm and artificial neural network. The ANN module is used to determine the spectrum state and optimize the traditional energy detection algorithm. GEO satellites are used to fuse the information sensed by LEO satellites and then give the spectrum decision, thereby realizing the inter-satellite spectrum state sensing. Finally, the sensing quality is evaluated by the analysis of sensing delay and sensing energy consumption. The simulation results show that our proposed algorithm has lower complexity, the sensing delay and sensing energy consumption compared with the traditional energy detection method.

• 한국통신학회논문지
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• 제35권5A호
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• pp.490-495
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• 2010

본 논문에서는 DFT를 활용한 순차적 스펙트럼 센싱 알고리즘을 제안한다. 기존의 FFT를 이용한 센싱 알고리즘의 경우 FFT의 특성상 한번에 모든 주파수 성분을 구하여 임계값과 비교하는 구조로 불필요한 계산량을 포함하고 있다. 제안하는 센싱 알고리즘에서는 DFT를 활용하여 우선순위에 따라서 주파수 성분을 순차적으로 구하고 이를 임계값과 비교하여 신호의 존재 여부를 판단한다. 제안하는 센싱 알고리즘은 기존의 FFT를 이용한 센싱 알고리즘과 유사한 검출 성능을 제공하면서 신호의 조기 검출 여부에 따라 스펙트럼 센싱에 필요한 계산량을 현저하게 줄일 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.200-203
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• 2006

Cloud detection algorithm is being developed as major one of the 16 baseline products of CMDPS (COMS Meteorological Data Processing System), which is under development for the real-time application of data will be observed from COMS Meteorological Imager. For cloud detection from satellite data, we studied two different algorithms. One is threshold technique based algorithm, which is traditionally used, and another is artificial neural network model. MPEF scene analysis algorithm is the basic idea of threshold cloud detection algorithm, and some modifications are conducted for COMS. For the neural network, we selected MLP with back-propagation algorithm. Prototype software of each algorithm was completed and evaluated by using the MTSAT-1R and GOES-9 data. Currently the software codes are standardized using Fortran90 language. For the preparation as an operational algorithm, we will setup the validation strategy and tune up the algorithm continuously. This paper shows the outline of the two cloud detection algorithm and preliminary test result of both algorithms.

• 대한원격탐사학회지
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• 제23권1호
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• pp.55-58
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• 2007

The prototype radiometric calibration algorithm of the imagers for IR channels has been developed according to the Weinreb's method. Applying the algorithm to the GOES-12 count data, we have shown that the calibration coefficients (slope and intercept) evaluated by the algorithm gives good agreement with the NESDIS's ones, and that the scanning error due to the scan mirror emissivity and stripe error are almost eliminated by the East/West angle dependent scan-mirror correction and the respective calculation of intercept for each North/South scan line, respectively.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 추계학술발표대회
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• pp.44-47
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• 2011

In this paper, we propose context-aware based on Low Power Sensing Algorithm. The proposed sensing algorithm reduces power consumptions using low-power sensing algorithms and low-power sensing protocols. Experimental results show that the average power consumption of the proposed method is up to half consumption that of the conventional method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.408-410
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• 2003

In this paper, an improved gradient direction assisted linking algorithm is proposed. This algorithm begins with initial seeds satisfying some local criteria. Then it will search along the direction provided by the initial point. A window will be generated in the gradient direction of the current point. Instead of the conventional method which only considers the value of the local salient structure, an improved mathematical model is proposed to describe the desired linear features. This model not only considers the value of the salient structure but also the direction of it. Furthermore, the linking problem under this model can be efficiently solved by dynamic programming method. This algorithm is tested for linear features detection in IKONOS images. The result demonstrates this algorithm is quite promising.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.1998-2016
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• 2012

Reliable spectrum sensing algorithm is a fundamental component in cognitive radio. In this paper, a non-cooperative spectrum sensing algorithm which needs only one cognitive radio node named CORDIC (Coordinate Rotation Digital Computer) Jacobi based method is proposed. The algorithm computes the eigenvalues of the sampled covariance of received signal mainly by shift and additional operations, which is suitable for hardware implementation. Based the latest random matrix theory (RMT) about the distribution of the limiting maximum and minimum eigenvalue ratio, the relationship between the probability of false alarm and the decision threshold is derived. Simulations and discussions show the method is effective. Real captured digital television (DTV) signals and Universal Software Radio Peripheral (USRP) are also employed to evaluate the performance of the algorithm, which prove the proposed algorithm can be applied in practical spectrum sensing applications.

• 대한의용생체공학회:의공학회지
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• 제23권6호
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• pp.477-484
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• 2002

A pacemaker autosense algorithm with dual thresholds. one for noise or tachyarrhythmia detection (noise threshold, NT) and the other for intrinsic beat detection (sensing threshold. ST), was developed to improve the sensing performance in single pass VDD electrograms. unipolar electrograms, or atrial fibrillation detection. When a deflection in an electrogram exceeds the NT (defined as 50% of 57), the autosense algorithm with dual thresholds checks if the deflection also exceeds the ST. If it does, the autosense algorithm calculates the signal to noise ratio (SNR) of the deflection to the highest deflection detected by NT but lower than ST during the last cardiac cycle. If the SNR 2, the autosense algorithm declares an intrinsic beat detection and calculates the next ST based on the three most recent intrinsic peaks. If the SNR $\geq$2, the autosense algorithm checks the number of deflections detected by NT during the last cardiac cycle in order to determine if it is a noise detection or tachyarrhythmia detection. Usually the autosense algorithm tries to set the 57 at 37.5% of the average of the three intrinsic beats, although it changes the percentage according to event classifications. The autosense algorithm was tested through computer simulation of atrial electrograms from 5 patients obtained during EP study, to simulate a worst sensing situation. The result showed that the ST levels for autosense algorithm tracked the electrogram amplitudes properly, providing more noise immunity whenever necessary. Also, the autosense algorithm with dual thresholds achieved sensing performance as good as the conventional fixed sensitivity method that was optimized retrospectively.

• Journal of information and communication convergence engineering
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• 제14권2호
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• pp.106-114
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• 2016

Differential sensing methods are more effective in alleviating panel noise than single-line sensing, and thus have been increasingly used in the touch screen industry. However, they have a drawback: they tend to cancel out multiple touches and need touch position recovery algorithms. This paper introduces a novel algorithm of touch position recovery for differential sensing, which is a low-complexity but high-accuracy approach for determining multiple touch positions. We have implemented the proposed method in a touch screen controller system on a chip. In the simulation experiments using realistic touch screen models and a differential sensing circuit, the algorithm exhibited a high detection performance of a signal-to-noise ratio gain of up to 52.21 dB. Therefore, we can conclude that the proposed method is substantially more accurate than the previous method. Further, the proposed method incurs little or no overhead in terms of the detection speed and the chip size.