• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.647-654
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• 2016

Indoor localization based on visible-light communication using the received signal strength intensity (RSSI) has been widely studied because of its high accuracy compared with other wireless localization methods. However, because the RSSI can vary according to the inclination and azimuth of the receiver, a large error can occur, even at the same position. In this paper, we propose a visible-light communication-based 3-D indoor positioning algorithm using the Gauss-Newton technique in order to reduce the errors caused by the change in the inclination of the receiver. The proposed system reduces the amount of computations by selecting the initial position of the receiver through the linear least-squares method (LSM), which is applied to the RSSIs, and improves the position accuracy by applying the Gauss-Newton technique to the 3-D nonlinear model that contains the RSSIs acquired by the changes in the azimuth and inclination of the receiver. In order to verify the validity of the proposed algorithm in an indoor space with dimensions of $6{\times}6{\times}3m$ where 16 LED lights are installed, we compare and analyze the errors of the conventional linear LSM-based trilateration technique and the proposed algorithm according to the changes in the inclination and azimuth of the receiver. The experimental results show that the location accuracy of the proposed algorithm is improved by 82.5% compared to the conventional LSM-based trilateration technique.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1883-1890
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• 2013

Location detection technology (LDT) is one of the core techniques for location based service (LBS) in wireless communication for improving resource management and quality of services. The location of a mobile station (MS) is estimated using the time of arrival (TOA) technique based on three circles with centers corresponding to coordinates of three base stations (BSs) and radius corresponding to distances between MS and BSs. For accurately estimating the location of MS, three circles should meet at a point for the trilateration method, but they generally do not meet a point because the radius is increased depending on the number of time delay for estimating the distance between MS and BS and the carrier frequency. The increased three circles intersect at six points and the three intersection points among them should be generally placed close to coordinate of the location for the specific MS. In this paper, we propose the shortest distance algorithm for TOA trilateration method, to select three interior intersection points from entire six points. The proposed approach selects three intersection points with the shortest distances between coordinates of MS and intersection points and determines the averaged coordinate of the selected three points, as the location of the specific MS. We demonstrate the performance of the proposed algorithm using a typical computer simulation example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.942-949
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• 2016

Efficient routing protocols designed for Wireless Sensor Networks (WSN) can be extended and applied to Internet of Things (IoT) data routing, as IoT can be considered to be an extension from WSN. When the size of the data in IoT is often bigger than in conventional WSNs, existing cluster routing protocol such as LEACH may cause high data loss rate due to its incomplete load balancing. We present an enhanced LEACH-based protocol which can minimize the data loss which is an important performance measure in IoT. In our proposed protocol, the base station estimates the location of nodes by the trilateration technique to make sure optimal number of cluster heads and members in a deterministic manner. We evaluate our proposed protocol via computer simulations in terms of data loss rate and average network lifetime.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.207-214
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• 2021

A new positioning technique for positioning of LTE base stations is proposed. The positioning information of the base station is absolutely necessary for model-based wireless positioning, and is required in some of the various merhodologies for estimating signals in an uncorrected area when construnting a database for fingerprinting-based positioning. Using the acquired location-based Reference Signal Received Power (RSRP) information to estimate the location of the base station, it is impossible with the existing trilateration methods. Therefore, in this paper, a method using reference particles is proposed. Particles are randomly generated in the application area, and signal propagation modeling is performed assuming that a base station is located in each particle. Based on this, the errors of measurements are calculated. The particle group with the minimum measurement errors is selected, the position of the base station is estimated through weighted summation, and the signal propagation model of the corresponding base station is built at the same time. The performance of the proposed technology is verified using data acquired in Seocho-dong, Seoul.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.11-16
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• 2023

As techniques for indoor positioning, fingerprinting, indoor positioning method using trilateration, and utilizing information obtained from equipments by Wi-Fi/Bluetooth, etc are common and representative methods to specify the user's indoor position. However, in these methods, an indoor space should be provided with enough space to install a large number of equipment (AP, Beacon). In this paper, we propose a technique that can express the user's location within a building by simultaneously using the GPS signal and the signal transmitted from the beacon in a building structure where the conventional method cannot be applied, such as a narrow building. A shortest path search system was designed and implemented by applying the Dijkstra Algorithm, one of the most representative and efficient shortest path search algorithms for shortest path search. The proposed technique can be considered as one of the methods for measuring the user's indoor location considering the structural characteristics of a building in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.85-95
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• 2019

This work shows how to design a robot structure and to control to overcome obstacles while traveling through ducts of various diameters and shapes by three-legged robot. Circuits are centered in the body to connect the three wheel bodies that are driven around the center body with the 4-section slider link structure. Also, the springs are used to contract and expand the robot legs so that it can be caparable of various environments. Geared motor, spring, and belt were selected based on the static and dynamic calculation to be suitable to horizontal and vertical travels. The center body is equipped with a camera and the distance sensors, and a control algorithms are implemented so that it can be successfully performed in L-type and T-type ducts. Using UWB modules and trilateration algorithm, the location of the duct-cleaning robot inside the duct could be identified successfully.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.243-245
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• 2021

Existing beacons are suitable for providing untact services, but they have the disadvantage of difficulty in accurate indoor positioning because the deviation in signal strength increases depending on the environment. In general, trilateration technique can reduce deviation, but if the distance between beacons is quite irregular, it becomes difficult to apply the algorithm. Therefore, in this paper, we studied how to reduce the signal power measurement error between beacons. First, we transformed the distance measurement formula using RSSI, assuming that the TX values were the same. In addition, we compared measurement errors with existing beacons by searching beacons with beacons scanner applications implemented with Android. As a result, it was confirmed that if a certain distance was further away, the measurement was measured more accurately than the non-changing beacon. Through this, accurate indoor positioning will be possible even in various disability situations. It is also expected that there will be more cases of establishing services that combine beacon with non-face-to-face services.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.2
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• pp.220-226
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• 2013

Recently, with the rapid development of factory automation and logistics system, a few workers were able to manage the broad workplace such as large vessels and warehouse. To estimate the exact location of these workers in the conventional wireless indoor localization systems, three or more fixed nodes are generally used to recognize the location of a mobile node consisting of a single node. However, these methods are inefficient in terms of node deployment because the broad workplace requires a lot of fixed nodes compared to workers(mobile nodes). Therefore, to efficiently deploy fixed nodes in these environments that need a few workers, this paper presents a novel estimation algorithm which can reduce the number of fixed nodes by efficiently recognizing the relative coordinates of two fixed nodes through a mobile node composed of three nodes. Also, to minimize the distance errors between mobile node and fixed node, rounding estimation(RE) technique is proposed. Experimental results show that the error rate of localization is improved, by using proposed RE technique, 90.9% compared to conventional trilateration in the free space. In addition, despite the number of fixed nodes can be reduced by up to 50% in the indoor free space, the proposed estimation algorithm recognizes precise location which has average error of 0.15m.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1294-1300
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• 2010

In an environment where all nodes move, the sensor node receives anchor node's position information within communication radius and modifies the received anchor node's position information by one's traveled distance and direction in saving in one's memory, where if there at least 3, one's position is determined by performing localization through trilateration. The proposed localization mechanisms have been simulated in the Matlab. In an environment where certain distance is maintained and nodes move towards the same direction, the probability for the sensor node to meet at least 3 anchor nodes with absolute coordinates within 1 hub range is remote. Even if the sensor node has estimated its position with at least 3 beacon information, the angle ${\theta}$ error of accelerator and digital compass will continuously apply by the passage of time in enlarging the error tolerance and its estimated position not being relied. Dead reckoning technology is used as a supplementary position tracking navigation technology in places where GPS doesn't operate, where one's position can be estimated by knowing the distance and direction the node has traveled with acceleration sensor and digital compass. The localization algorithm to be explained is a localization technique that uses Dead reckoning where all nodes are loaded with omnidirectional antenna, and assumes that one's traveling distance and direction can be known with accelerator and digital compass. The simulation results show that our scheme performed better than other mechanisms (e.g. MCL, DV-distance).

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1483-1495
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• 2007

Thanks to IEEE 802.11 technique, accessing Internet through a wireless LAN(Local Area Network) is possible in the most of the places including university campuses, shopping malls, offices, hospitals, stations, and so on. Most of the APs(access points) for wireless LAN are supporting 2.4 GHz band 802.11b and 802.11g protocols. This paper is introducing a C# library function which can be used to read RSSIs(Received Signal Strength Indicator) from APs. An LBS(Location Based Service) estimates the current location of the user and provides useful user's location-based services such as navigation, points of interest, and so on. Therefore, indoor, LBS is very desirable. However, an indoor LBS cannot be realized unless indoor position ing is possible. For indoor positioning, techniques of using infrared, ultrasound, signal strength of UDP packet have been proposed. One of the disadvantages of these techniques is that they require special equipments dedicated for positioning. On the other hand, wireless LAN-based indoor positioning does not require any special equipments and more economical. A wireless LAN-based positioning cannot be realized without reading RSSIs from APs. Therefore, our C# library function will be widely used in the field of indoor positioning. In addition to providing a C# library function of reading RSSI, this paper introduces implementation of indoor positioning modules making use of the library function. The methods used in the implementation are K-NN(K Nearest Neighbors), Bayesian and trilateration. K-NN and Bayesian are kind of fingerprinting method. A fingerprint method consists of off-line phase and realtime phase. The process time of realtime phase must be fast. This paper proposes a decision tree method in order to improve the process time of realtime phase. Experimental results of comparing performances of these methods are also discussed.