• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1856-1864
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• 2015

In this paper, the localization algorithm for improving the accuracy of the positioning using the Wi-Fi fingerprint using the normal distribution probability and the built-in typed accelerometer sensor, the gyroscope sensor of smartphone in the indoor environment is proposed. The experiments for analyzing the performance of the proposed algorithm were carried out at the region of the horizontal and vertical 20m * 10m in the engineering school building of our university, and the performance of the proposed algorithm is compared with the fingerprint and the DR (dead reckoning) while user is moving according to the assigned region. As a result, the maximum error distance in the proposed algorithm was decreased to 2cm and 36cm compared with two algorithms, respectively. In addition to this, the maximum error distance was also less than compared with two algorithms as 16.64cm and 36.25cm, respectively. It can be seen that the fingerprint map searching time of the proposed algorithm was also reduced to 0.15 seconds compared with two algorithms.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.457-458
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• 2012

최근 무선으로 실내위치를 측정하는 방법으로 WiFi를 많이 사용하고 있다. WiFi를 이용하여 실내에서의 위치를 파악하는 것에서 끝나지 않고 이를 실시간으로 모니터링 함으로써 긴박한 인명구조의 상황이나 전시상황에서 사용하고자 한다. 기본 안드로이드 단말기(클라이언트)와 서버간의 통신에 의해서 클라이언트는 위치를 전송하고 서버는 이를 이용하여 실시간으로 현재위치를 파악 할 수 있도록 사용자에게 표시를 해준다. 향후 개발과정에서 실외위치 모니터링 기능까지 포함하도록 확장할 예정이다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.8
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• pp.663-673
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• 2013

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on IMU deployed in smart phone, we develop a hybrid positioning estimation framework with a combination of WPS. The developed approaches can strengthen the advantages of independent indoor applicability of IMU. The estimation of IMU is efficiently compensated by radio fingerprint based Wi-Fi Positioning System. We put a focus especially on the hybrid algorithmic framework. Compared on the existing approaches of WPS or IMU, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.58-63
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• 2015

Due to GPS signal's vulnerability of jamming attack, various enhancement techniques are needed. Among variety of techniques, we focused on GPS receiver's anti-jamming techniques. There are many anti-jamming methods at GPS receivers which include filtering methods in time domain, frequency domain and space domain. However, these methods are ineffective to signals, which include both jamming and noise. To solve the problem, this paper proposes a jamming separation scheme by using a BSS method in a jamming environment. As separated GPS signals include noise after the jamming separation method, it is difficult to receive accurate GPS signals. For this reason, this paper also proposes a wavelet de-noising method to effectively eliminate noise. Experimental results of this paper are based on a real field test data of an integrated GPS/QZSS/Wi-Fi positioning system. At the end, the simulation result demonstrates its superiority by showing improved positioning accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.84-92
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• 2009

In this paper, using the received signal strength of radio beacon such as Wi-Fi, Bluetooth, CDMA and GPS signal from the satellite, we propose the system of positioning which considered indoor and outdoor based on the Place Lab. Conventional Place Lab utilize the various positioning parameters to estimate the indoor location. However, this conventional system has limitations with respect to the range and efficiency of usage. Therefore, we defined the converged model of multisensor data and re-organized the Place Lab to overcome the limitation of a conventional system. Proposed system uses the radio beacon signal and GPS signal together to estimate the location. Furthermore, it provides the seamless PNS service with many mobile devices because this system realized by the OSGi bundle. This proposed system has evaluated the performance with SAMSUNG T*OMNIA SCH-M490 smart phone and the result shows the system is able to support the PNS service.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.25-30
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• 2024

Smart City, a key application area of the AIoT (Artificial Intelligence of Things), provides various services in safety, security, and healthcare sectors through location tracking and location-based services. an IPS (Indoor Positioning System) is required to implement location-based services, and wireless communication technologies such as WiFi, UWB (Ultra-wideband), and BLE (Bluetooth Low Energy) are being applied. BLE, which enables data transmission and reception with low power consumption, can be applied to various IoT devices such as sensors and beacons at a low cost, making it one of the most suitable wireless communication technologies for indoor positioning. BLE utilizes the RSSI (Received Signal Strength Indicator) to estimate the distance, but due to the influence of multipath fading, which causes variations in signal strength, it results in an error of several meters. In this paper, we conducted research on a path loss model that can be applied to BLE IPS for proximity services, and confirmed that optimizing the free space propagation loss coefficient can reduce the distance error between the Tx and Rx devices.

• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.33-40
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• 2017

In this paper, we introduce commercial indoor navigation systems being deployed and serviced in many fields of industry focusing on their indoor positioning technologies. Indoor positioning technology is a technology that locates people or targets in the interior of a building. To do that, it utilizes radio waves such as WiFi, and bluetooth, magnetic fields, or other sensory information from smart phones. We present indoor navigation systems categorizing them into their indoor positioning technologies. We define important performance issues for indoor positioning technologies and analyze them according to the performance issues. We believe that this paper provide wise view and necessary information for recent indoor navigation systems.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.169-173
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• 2020

Location-based services are used as core services in various fields. In particular, in the field of public services such as emergency rescue, accurate location estimation technology is very important. Recently, the technology of tracking the location of self-isolation subjects for COVID-19 has become a major issue. Therefore, location estimation technology using personal smart devices is being studied in various ways, and the most widely used method is to use GPS. Other representative methods are using Wi-Fi, Pedestrian Dead Reckoning (PDR), Bluetooth Low Energy (BLE) beacons, and LTE signals. In this paper, we introduced a positioning technology using deep learning based on LTE Channel State Information-Reference Signal (CSI-RS) data, and confirmed the possibility through an outdoor location estimation experiment using a commercial LTE signal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.25-31
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• 2017

The indoor location based service proposed in the study was assigned to target a moving user. Positioning in the outdoor environment is accurate while using GPS. However, in an indoor environment, positioning is inaccurate and difficult. In order to overcome this, studies of various techniques for positioning based on wireless communication such as Wi-Fi, Zigbee and Bluetooth are being performed. The RSSI value and the delivery signal of the bluetooth beacon are measured according to the distance, and to a database. It was applied calculating the value for the average RSSI and the RSSI filtering feedback. Filtering is used to reduce the error of the RSSI values that are measured at long distance. When average and feedback filtering coefficient are set with 0.5, irregular and highly RSSI values are decreased. As the distance increases, the range of error is confirmed to have a reduction when using a distance calculation correction algorithm. Finally, when using the RSSI measurement results filtering, it corrects an unstable signal. Also, the distance correction algorithm is used to reduce a range of errors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.