• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.233-247
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• 2023

Recently, research on detecting objects in hidden spaces beyond the direct line-of-sight of observers has received attention. Most studies use optical equipment that utilizes the directional of light, but sound that has both diffraction and directional is also suitable for non-line-of-sight(NLOS) research. In this paper, we propose a novel method of detecting objects in non-line-of-sight (NLOS) areas using acoustic signals in the audible frequency range. We developed a deep learning model that extracts information from the NLOS area by inputting only acoustic signals and predicts the properties and location of hidden objects. Additionally, for the training and evaluation of the deep learning model, we collected data by varying the signal transmission and reception location for a total of 11 objects. We show that the deep learning model demonstrates outstanding performance in detecting objects in the NLOS area using acoustic signals. We observed that the performance decreases as the distance between the signal collection location and the reflecting wall, and the performance improves through the combination of signals collected from multiple locations. Finally, we propose the optimal conditions for detecting objects in the NLOS area using acoustic signals.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.2
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• pp.108-116
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• 2011

Non-line-of-sight (NLOS) error is the most common and also a major source of errors in wireless location system. A novel weighting factor (NWF) method is presented in this paper, based on the RSS(Received Signal Strength) measurements, path loss model and Circular Disk of Scatterers Model (CDSM). The proposed positioning method effectively weighted the TOA distance measurements for each Base Station (BS). Simulation results show that the proposed method efficiently weighted the distance measurements and achieve higher localization accuracy than that of Linear Line of Position (LLOP) and Believable Factor Algorithm (BFA).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4698-4716
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• 2017

Wireless signal transmission is influenced by environmental effects. These effects have also been challenging for Vehicular Ad hoc Network (VANET) in real-time communication. More specifically, in an urban environment, with high mobility among vehicles, a vehicle's status from the transmitter can instantly trigger from line of sight to non-line of sight, which may cause loss of real-time communication. In order to overcome this, a deterministic signal propagation model is required, which has less complexity and more feasibility of implementation. Hence, we propose a realistic path loss model which adopts ray tracing technique for VANET in a grid urban environment with less computational complexity. To evaluate the model, it is applied to a vehicular simulation scenario. The results obtained are compared with different path loss models in the same scenario based on path loss value and application layer performance analysis. The proposed path loss model provides higher loss value in dB compared to other models. Nevertheless, the performance of vehicle-vehicle communication, which is evaluated by the packet delivery ratio with different vehicle transmitter density verifies improvement in real-time vehicle-vehicle communication. In conclusion, we present a realistic path loss model that improves vehicle-vehicle wireless real-time communication in the grid urban environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1248-1253
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• 2010

In this paper, the compensation algorithm for localization using the concept of equivalent distance rate(AEDR) in order to compensate ranging error in the SDS-TWR(Symmetric Double-Sided Two-Way Ranging) is proposed and the performance of the proposed algorithm is analyzed by the localization experiments. The ranging error of the SDS-TWR in the distance between mobile node and beacon node is measured to average 1m~8m by ranging experiments. But it is confirmed that the performance of the localization by the AEDR is better than that of the SDS-TWR 4 times in university auditorium and corridor, and the localization error of above 3~10m is reduced to average 2m and that of below 3m is reduced to average 1m respectively. It is concluded that the AEDR is superior to the NLOS(Non Line Of Sight) than LOS(Line Of Sight) in performance of ranging compensation for localization, and the AEDR is more helpful to localization systems practically considering the environment of sensor networks is under NLOS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.950-961
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• 2004

In this paper, we measured and analyzed propagation characteristics in a subway tunnel that is recently increasingly becoming one of the radio communication environments. The measurements are carried out in a subway tunnel with frequency bands of 2.45㎓ and 5.8㎓. The length of tunnel we used for this study is 175m of LOS (Line-of-sight) and 270m of NLOS (Non Line-of-Sight). The subway tunnel is curved and its cross section is horseshoe type. The measurement systems we employ in this study are a narrow-band system and a wide-band system. The narrow-band system is used to get path loss measurement and the wide-band system is used to figure out delay profile measurement. In particular, the wide-band system consists of 1023 length PN sequence generator using a chip rate of 80MHz based on a sliding correlation technique. The omni-directional antennas and directional antennas are used to analyze propagation characteristics for beam type of antenna. The path loss displays only pure path loss of a tunnel environment. The delay profile indicates the mean excess delay and RMS (root mean square) delay spread.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.444-452
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• 2017

Recently, a demand of Internet-of-things (IoT) rises dramatically and an interest in Low Power Wide Area (LPWA) grows larger accordingly. In this paper, performance in LoRa which is included in LPWA standard is analyzed. Particularly, after measuring Received Signal Strength Indication (RSSI) of received signal on Line-of-sight (LoS) and Non-line-of-sight (NLoS) environment and it is compared with RSSI which theoretical path loss model is applied to. Among many path loss models, the simulation for theoretical RSSI use Log-distance, Two-ray model and Okumura-Hata model that is based on the test database. Consequently, the result of Okumura-Hata model is the most similar with the measured RSSI. When a network based on LoRa is built, this result can used to decide optimal node arrangement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.91-97
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• 2018

This paper presents implementation possibilities of digital IoT doorlock systems via VLC(Visible Light Communication)'s color grid. The color grid-based VLC modulation scheme which are discussed in this paper utilize the straightness of light and abundant frequency resources which are the properties of the light. Performance results in this paper are compared to that of conventional modulations with Bit Error Rate (BER) and Signal to Noise Ratio (SNR) simulations. With respect to a channel model, the proposed modulation schemes select the nearest Line Of Sight (LOS) except Non Line Of Sight (NLOS). Experiments in this paper show error rates of received symbols by changing power dB at a distance of 3m between Tx and Rx in an indoor environment. Through performance results and experiments, this paper demonstrates superiority of the proposed color grid-based modulation schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.87-95
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• 2010

In this paper, we propose an improved TDoA (Time Difference of Arrival) localization scheme using PSO (Particle Swarm Optimization) in UWB (Ultra Wide Band) systems. The proposed scheme is composed of two steps: re-estimation of TDoA parameters and re-localization of a tag position. In both steps, the PSO algorithm is employed to improve the performance. In the first step, the proposed scheme re-estimates the TDoA parameters obtained by traditional TDoA localization to reduce the TDoA estimation error. In the second step, the proposed scheme with the TDoA parameters estimated in the first step, re-localizes the tag to minimize the location error. The simulation results show that the proposed scheme achieves a more superior location performance to the traditional TDoA localization in both LoS (Line-of-Sight) and NLoS (Non-Line-of-Sight) channel environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1177-1184
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• 2008

Non-line-of-sight (NLOS) propagation can severely weaken the accuracy of ranging and localization in wireless location systems. NLOS bias mitigation techniques have recently been proposed to relieve the NLOS effects, but positively rely on the capability to accurately distinguish between LOS and NLOS propagation scenarios. This paper proposes an energy-capture-based NLOS identification method for LDR-UWB systems, based on the analysis of the characteristics of the channel impulse response (CIR). With this proposed energy capture method, the probability of successfully identifying NLOS is much improved than the existing methods, such as the kurtosis method, the strongest path compare method, etc. This NLOS identification method can be employed in adaptive modulation scheme to decrease bit error ratio (BER) level for certain signal-to-noise ratio (SNR). The BER performance with the adaptive modulation can be significantly enhanced by selecting proper modulation method with the knowledge of channel information from the proposed NLOS identification method.

• Journal of IKEEE
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• v.20 no.1
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• pp.1-8
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• 2016

In this paper, we propose an effective time-of-arrival (TOA)-based localization method with adaptive bias computation in indoor environments. The goal of the localization is to estimate an accurate target's location in wireless localization system. However, in indoor environments, non-line-of-sight (NLOS) errors block the signal propagation between target device and base station. The NLOS errors have significant effects on ranging between two devices for wireless localization. In TOA-based localization, finding the target's location inside the overlapped area in the TOA-circles is difficult. We present an effective localization method using compensated distance with adaptive bias computation. The proposed method is possible for the target's location to estimate an accurate location in the overlapped area using the measured distances with subtracted adaptive bias. Through localization experiments in indoor environments, estimation error is reduced comparing to the conventional localization methods.