• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.489-493
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• 2010

In an indoor localization method taking the lateration-based approach, the distance between a target and an AP (Anchor Point) is estimated using RSS (Received Signal Strength) measurements. Since the characteristics of a radio signal randomly vary in time and space, errors are unavoidable in distance estimation with measured RSS. Since the accuracy of distance estimation affects the localization accuracy of a lateration-based method, additional APs hearing a target have been used for localization in the literature. However, lots of experimental results show that the accuracy of a lateration-based method is improved by using carefully selected APs measuring the high quality RSSs which the distances estimated is close to the actual distances between nodes as reference APs, not using merely more APs. In this paper, we focus on selection method of reference AP and distance estimation method reflecting on environmental dynamics. We validate our method by implementing an indoor localization system and evaluating the accuracy of our method in the various experimental environments.

• The KIPS Transactions:PartC
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• v.17C no.3
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• pp.251-258
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• 2010

In an indoor localization method taking the lateration-based approach, the location of a target is estimated with the location of anchor points (APs) and the approximated distances between the target and APs using received signal strength (RSS) measurements. The accuracy of distance estimation affects the localization accuracy of a lateration-based method. Since a radio propagation environment varies randomly in time and space, the highest RSSs do not necessarily give the best estimation of the distances between a target and APs. Thus, all APs hearing a target have been used for localization. However, the accuracy of a lateration-based method degrades if more APs beyond a certain threshold are used because the area of polygon with the APs increases. In this paper, we focus on reducing the size of the polygon to further increase the localization accuracy. We use the centroid of the polygon as a reference point to estimate the relative location of a target in the polygon. Once the relative location is estimated, only the APs which are closest to the target are used for localization to reduce the area of the polygon with the APs. We validate the proposed method by implementing an indoor localization system and evaluating the accuracy of the proposed method in the various experimental environments.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.9
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• pp.856-860
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• 2006

A CCD camera is used to determine the position of the point sources that influence the measurement accuracy in the absolute interferometer. The principle of determination method is based on the GPS in which the position is determined by more than 3 distance information from the known positions. Two-dimensional array of photo-detectors in the CCD camera is used as known positions. Performing optimization of the cost function constructed with phase values measured at each pixel on the CCD camera, the position coordinates of each source is precisely determined.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.45-61
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• 2010

In the communication channel, the received signal is affected by many factors that can cause errors. These effects mean that received signal strength (RSS) based methods incur more errors in measuring distance and consequently result in low precision in the location detection process. As one of the approaches to overcome these problems, we propose using direction calibration to improve the performance of the RSS-based method for distance measurement, and sequentially a weighted least squares (WLS) method using reliability factors in conjunction with a conventional RSS weighting matrix is proposed to solve an over-determined localization process. The proposed scheme focuses on the features of the RSS method to improve the performance, and these effects are proved by the simulation results.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.208-215
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• 2013

Early iterations of the existing Global Positioning System (GPS)-based or radio lateration technique-based vehicle localization algorithms suffer from flip ambiguities, forged relative location information and location information exchange overhead, which affect the subsequent iterations. This, in turn, results in an erroneous neighbor-vehicle map. This paper proposes an extended information overlap measure (EIOM) algorithm to reduce the flip error rates by exchanging the neighbor-vehicle presence features in binary information. This algorithm shifts and associates three pieces of information in the Moore neighborhood format: 1) feature information of the neighboring vehicles from a vision-based environment sensor system; 2) cardinal locations of the neighboring vehicles in its Moore neighborhood; and 3) identification information (MAC/IP addresses). Simulations were conducted for multi-lane highway scenarios to compare the proposed algorithm with the existing algorithm. The results showed that the flip error rates were reduced by up to 50%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.1012-1017
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• 2008

Recently, the use of wireless fan is increased by the development of wireless communication and convenience. Moreover, it makes an issue of security threat and vulnerability of wireless tan. Therefore, the IEEE established new standard such as 802.11i in 802.11 to supplement security vulnerability of wireless tan. But the security threat that does not solve, still remains. In this paper, we proposed that the location detection algorithm, that is used Kalman-Filter, Lateration and RSSI, and the mechanism that detects security status of AP and unauthorized AP by using beacon-frame of AP in building. Finally, we confirmed performance of proposed algorithm is good in comparison of established algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4408-4428
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• 2019

Due to the rapid advancement in smart phones, numerous new specifications are developed for variety of applications ranging from health monitoring to navigations and tracking. The word indoor navigation means location identification, however, where GPS signals are not available, accurate indoor localization is a challenging task due to variation in the received signals which directly affect distance estimation process. This paper proposes a hybrid approach which integrates fingerprinting based K-Nearest Neighbors (K-NN) and lateration based MinMax position estimation technique. The novel idea behind this hybrid approach is to use Euclidian distance formulation for distance estimates instead of indoor radio channel modeling which is used to convert the received signal to distance estimates. Due to unpredictable behavior of the received signal, modeling indoor environment for distance estimates is a challenging task which ultimately results in distance estimation error and hence affects position estimation process. Our proposed idea is indoor position estimation technique using Bluetooth enabled smart phones which is independent of the radio channels. Experimental results conclude that, our proposed hybrid approach performs better in terms of mean error compared to Trilateration, MinMax, K-NN, and existing Hybrid approach.