• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.811-820
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• 2012

GNSS signal is vulnerable to jamming signal because of well-known signal structure and weak signal power. For these reasons, the need for analysis of jamming effects and anti-jamming techniques of is increasing. In this paper, a GNSS signal generator is designed which includes a radio wave propagation model for six kind of tactical environments and a body masking model for the reception environment of a vehicle. The radio wave propagation model for downtown, rural, forest, coastline, waste land and snow or ice area is designed using two-ray model. The body masking model is designed the effect which the antenna is affected by the reception environment of a vehicle and radiation pattern from a user configuration. The performance of generated signals from the GNSS signal generator considering reception environment of a vehicle is evaluated by a commercial GPS L1 receiver(NordNav) in normal and jamming environment. Also, the generated GNSS signal is compared to a commercial GPS L1 H/W based RF signal generator(STR4500). The results show that the designed GNSS signal generator in a normal environment compared to the same navigation performance. In jamming environment, it is shown that the body masking effect and GNSS signal acquisition and tracking loss in compliance with the jamming signal are precisely working in the reception environment of a vehicle.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4934-4949
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• 2015

The unstable characteristic values of communication signals along with the varying SNR (Signal Noise Ratio) environment make it difficult to identify the modulations of signals. Most of relevant literature revolves around signal recognition under stable SNR, and not applicable for signal recognition at varying SNR. To solve the problem, this research developed a novel communication signal recognition algorithm based on Holder coefficient and cloud theory. In this algorithm, the two-dimensional (2D) Holder coefficient characteristics of communication signals were firstly calculated, and then according to the distribution characteristics of Holder coefficient under varying SNR environment, the digital characteristics of cloud model such as expectation, entropy, and hyper entropy are calculated to constitute the three-dimensional (3D) digital cloud characteristics of Holder coefficient value, which aims to improve the recognition rate of the communication signals. Compared with traditional algorithms, the developed algorithm can describe the signals' features more accurately under varying SNR environment. The results from the numerical simulation show that the developed 3D feature extraction algorithm based on Holder coefficient cloud features performs better anti-noise ability, and the classifier based on interval gray relation theory can achieve a recognition rate up to 84.0%, even when the SNR varies from -17dB to -12dB.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.379-385
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• 2020

The satellite employs an adaptive beamformer to efficiently detect various signals and to suppress multiple interference signals, simultaneously. Although the adaptive beamforming satellite system needs Angle-of-Arrival (AOA) information of the desired signal, it is difficult to estimate the signal AOAs on the satellite environment. However, the AOA estimation on the ground control tower is more efficient and accurate comparing to the satellite environment. In this paper, we propose an adaptive beamforming satellite system based on the signal location information on the ground, consisting on an angle estimator, an adaptive beamformer, and signal processing & D/B unit. The ground control tower estimates the accurate location of the signal source, and it sends the estimated coordinates of the desired signal to the satellite. The angle estimator mounted on the satellite calculates the desired signal AOA, based on the signal location information transmitted from the ground control center. The satellite beamformer detects the desired signal and suppresses unwanted signals based on the signal AOA calculated by the angle estimator. We provide computer simulation results to present the performance of the proposed satellite adaptive beamforming system based on the signal location information.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.107-112
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• 2006

The previous acquisition method of GPS receiver for reference station adopts not only the coherent integration method but also the non-coherent integration method in order to enhance sensitivity under noisy environment. However, under noisy environment, the previous GPS signal acquisition method causes the non-coherent integration loss which is a major factor among losses that can be caused during GPS signal acquisition. The non-coherent integration loss also increases with the strength of the received noise. This paper has intention of analyzing the performance of the GPS signal acquisition method proposed to effectively enhance sensitivity of DGPS reference receiver under noisy environment. This paper presents that the proposed GPS signal acquisition method suppresses the non-coherent integration loss through post-processing simulation. Furthermore, with regard to the mean acquisition time, it is shown that the number of search cells of the proposed GPS signal acquisition method is much fewer than that of the previous GPS signal acquisition method.

• Proceedings of the IEEK Conference
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• summer
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• pp.27-30
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• 2004

OFDMA is considered as one of the major candidates for broadband wireless access. The OFDMA signal is usually coherently demodulated, requiring the channel estimation which can be estimated using a known pilot signal. In multi-cell environment, the performance of channel estimation is mainly limited by intercell interference. It is desirable to use a pilot signal that can estimate the channel information robust to the intercell interference in the OFDMA uplink system. In this paper, we consider two types of pilot signal applicable to multi-cell OFDMA uplink systems: One is time-multiplexed pilot signal and the other is code­multiplexed pilot signal. Simulation results show that the code-multiplexed pilot is suitable for low mobility environment and time-multiplexed pilot is suitable for high mobility environment.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.125-134
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• 2009

Recently, as IT technology and the ubiquitous environment have diffused, the application of these techniques are being attempted in the field of traffic operations and management. Therefore, it is necessary to develop data collection systems and signal control strategies that are suitable in the ubiquitous environment and that will improve efficiency and safety of signalized intersections. The authors conducted a study on the Wireless Sensor Network (WSN) signal control strategy using a wireless communication network between individual vehicles and a signal-control system and full actuated signal control technique to propose a new signal control strategy in the ubiquitous environment. The WSN was defined to evaluate the algorithm used with PARAMICS API simulation. The simulation produced results that the WSN signal control is more effective than other signal control methods. The WSN signal control could reduce vehicle delay time to a maximum of 64% in comparison with other signal control methods in low and near saturation flow conditions.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.324-334
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• 2023

In this paper, the target simulator for RF signals was developed by using VST(Vector Signal Transceiver) and set by real-time signal processing SW programs. A function to process RF signals using FPGA(Field Programmable Gate Array) board was designed. The system functions capable of data processing, raw signals monitoring, target signals(simulated range, velocity) generating and RF environments data analyzing were implemented. And the characteristics of modulated signal were analyzed in RF environment. All function of programs for processing RF signal have options to store signal data and to manage the data. The validity of the signal simulation was confirmed through verification of simulated signal results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.1-10
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• 2019

Traffic Signal Evaluation HILS is a system designed to evaluate a traffic signal system, and has a function of driving that simulates a real environment using a simulator that simulates a real traffic signal environment and an LCS that simulates a traffic signal controller. This study simulates the function of the traffic signal controller and is designed for design the LCS which is connected to the center system and the traffic simulator (VISSIM). The design of the LCS program uses a portable python language, and the code is designed in two versions running on Windows in the PC environment and unning on embedded environment, with a slight modification of the code. In this study, we analyzed the limitations of using LCS on Windows in PC environment and confirmed the ease of simulation Linux in embedded environment at large capacity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3789-3809
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• 2014

Radio environment maps (REMs) and geolocation database represent an important source of information for the operation of cognitive radio networks, replacing or complementing spectrum sensing information. This paper provides a survey of methods for constructing the radio frequency layer of radio environment map (RF-REM) using distributed measurements of the signal levels at a given frequency in space and time. The signal level measurements can be obtained from fixed or mobile devices capable of sensing radio environment and sending this information to the REM. The signal measurements are complemented with information already stored in different REM content layers. The combined information is applied for estimation of the RF-REM layer. The RF-REM construction methods are compared, and their advantages and disadvantages with respect to the spatial distribution of signal measurements and computational complexity is given. This survey also indicates possible directions of further research in indirect RF-REM construction methods. It emphasizes that accurate RF-REM construction methods should in the best case support operation with random and clustered signal measurements, their operation should not be affected by measurements outliers, and it must estimate signal levels comparably on all RF-REM locations with moderate computational effort.