• Journal of Positioning, Navigation, and Timing
• /
• v.12 no.1
• /
• pp.1-9
• /
• 2023

The problem of classifying a non-line-of-sight (NLOS) signal in a multipath channel is important to improve global navigation satellite system (GNSS) positioning accuracy in urban areas. Conventional deep learning-based NLOS signal classifiers use GNSS satellite measurements such as the carrier-to-noise-density ratio (CN_0), pseudorange, and elevation angle as inputs. However, there is a computational inefficiency with use of these measurements and the NLOS signal features expressed by the measurements are limited. In this paper, we propose a Convolutional Neural Network (CNN)-based NLOS signal classifier that receives successive Auto-correlation function (ACF) outputs according to a time-series, which is the most primitive output of GNSS signal processing. We compared the proposed classifier to other DL-based NLOS signal classifiers such as a multi-layer perceptron (MLP) and Gated Recurrent Unit (GRU) to show the superiority of the proposed classifier. The results show the proposed classifier does not require the navigation data extraction stage to classify the NLOS signals, and it has been verified that it has the best detection performance among all compared classifiers, with an accuracy of up to 97%.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.2B
• /
• pp.217-227
• /
• 2004

With a rapid growth in the Internet technology, the network traffic is increasing swiftly. As for the increase of traffic, it had a large influence on performance of a total network. Therefore, a traffic management became an important issue of network management. In this paper, we study a forecast plan of network traffic in order to analyze network traffic and to establish efficient correspondence. We use time series forecast models and determine fitness whether the model can forecast network traffic exactly. In order to predict a model, AR, MA, ARMA, and ARIMA must be applied. The suitable model can be found that can express the nature of traffic for the forecast among these models. We determines whether it is satisfied with stationary in the assumption step of the model. The stationary can get the results by using ACF(Auto Correlation Function) and PACF(Partial Auto Correlation Function). If the result of this function cannot satisfy then the forecast model is unsuitable. Therefore, we are going to get the correct model that is to satisfy stationary assumption. So, we proposes a way to classify in order to get time series materials to satisfy stationary. The correct prediction method is managed traffic of a network with a way to be better than now. It is possible to manage traffic dynamically if it can be used.

• The Journal of the Acoustical Society of Korea
• /
• v.31 no.3
• /
• pp.115-128
• /
• 2012

This paper investigates the effects of diffuser on the acoustical parameters in music hall with consideration of the result of scattering coefficient measurement. A scale model hall of 600 seats with orchestra shell was used for experiments. The materials of 1:50 scale model was chosen through absorption coefficient measurement based on ISO 354. The model was matched to the computer simulation model in terms of reverberation time. In order to evaluate the effect of diffuser location, the measurements were accomplished with and without diffusers according to 7 configurations by diffuser-installed region; sidewall, balcony front, ceiling and so on. The following acoustical parameters were extracted from each measurement case; Reverberation time (RT), Early decay time (EDT), Clarity (C80), Center time (Ts), Sound strength (G) and Temporal diffusion (TD) from the auto-correlation function (ACF) of impulse responses. As a result, the absorption power and diffusion power were increased with number of diffusers. Accordingly RT, EDT and G were decreased by diffuser and the redirection of reflections was occurred briskly. Averaged TD was 6.05 to 6.30 by measurement cases. RT was found to be the most related factor to diffusion power (R = 0.94). The correlation between TD and EDT was high (R = 0.73). In addition, the effects of diffuser-installed location were discussed in terms of acoustical parameter variation.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_2
• /
• pp.1819-1827
• /
• 2021

Land-use/cover change caused by rapid urbanization in South Korea is one of the concerns in flood risk management because groundwater recharge by precipitation hardly occurs due to an increase in impermeable surfaces in urban areas. This study investigated the hydrologic effects of land-use/cover on groundwater recharge in the Yeonje-gu district of Busan, South Korea. A statistical time series analysis was conducted with temporal variations of precipitation and groundwater level to estimate lag-time based on correlation coefficients calculated from auto-correlation function (ACF), cross-correlation function (CCF), and moving average (MA) at five sites. Landform and land-use/cover within 250 m radius of the monitoring wells(GW01, GW02, GW03, GW04, and GW05) at five sites were identified by land cover and digital map using Arc-GIS software. Long lag-times (CCF: 42-71 days and MA: 148-161 days) were calculated at the sites covered by mainly impermeable surfaces(GW01, GW03, and GW05) while short lag-times(CCF: 4 days and MA: 67 days) were calculated at GW04 consisting of mainly permeable surfaces. The results suggest that lag-time would be one of the good indicators to evaluate the effects of land-use/cover on estimating groundwater recharge. The results of this study also provide guidance on the application of statistical time series analysis to environmentally important issues on creating an urban green space for natural groundwater recharge from precipitation in the city and developing a management plan for hydrological disaster prevention.