• Journal of KIISE:Information Networking
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• v.36 no.1
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• pp.24-33
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• 2009

In patch-and-stitch localization algorithms, a flip error refers to the kind of error in which a patch is stitched to the map as being wrongly reflected. In this paper, we present an anchor-free localization algorithm which tries to detect and prevent flip errors. The flip error prevention is achieved by two filtering mechanisms: the flip-ambiguity test and the flip-conflict detection. We evaluate the performances of proposed techniques though simulations and show that they achieve significant performance improvements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.19-25
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• 2013

In this paper, we proposed an enhanced monopulse MIMO radar system for the tactical scenario where the ground receivers are connected wireless backhaul and closely spaced. By applying the ${\alpha}{\beta}$ filter to the conventional monopulse MIMO radar, we show that the localization performance can be improved significantly. We also propose an efficient localization algorithm for a system with lower rate feedback. Using numerical simulations, we demonstrate that the proposed scheme can improve the localization performance while reducing the feedback over conventional scheme.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.21-26
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• 2012

This paper presents a real-time image transferring and localization system utilizing HSDPA, a commercial wireless network system. A novel image compression algorithm is developed based on MPEG4 to comply with uploading bandwidth of 130 kbps and QVGA image transmission of 30 fps. Aiming at being embedded in moving vehicles, the proposed system has a small size, low power consumption, and robustness to disturbances. We validate the performance of the system by presenting captured images of transferring video and localization data. Our system can be applied to real-time surround monitoring in moving vehicles or real-time ecology observation in remote places.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1314-1320
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• 2008

Recently, LBS(Location Based Service) which provides useful service based on the location of objects or human has drawn the attention of the research community. To provide LBS, many researchers have proposed many localization systems such as Cricket or Ubisense, however, these systems have the limit that it is very hard to perform the complicated computation on these systems because these systems consist of sensor nodes which have very limited computing power. In the paper, we propose a new localization system with the gateway node which has very high computing power and resource which is suitable for the complicated computation needed for localization.

• Proceedings of the Korean Information Science Society Conference
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• 2010.11a
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• pp.99-100
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• 2010

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.92-102
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• 2017

In this paper, we consider a typical health care system via the help of Wireless Sensor Network (WSN) for wireless patient tracking. The wireless patient tracking module of this system performs localization out of samples of Received Signal Strength (RSS) variations and tracking through a Particle Filter (PF) for WSN assisted by multiple transmit-power information. We propose a modified PF, Kullback-Leibler Distance (KLD)-resampling PF, to ameliorate the effect of RSS variations by generating a sample set near the high-likelihood region for improving the wireless patient tracking. The key idea of this method is to approximate a discrete distribution with an upper bound error on the KLD for reducing both location error and the number of particles used. To determine this bound error, an optimal algorithm is proposed based on the maximum gap error between the proposal and Sampling Important Resampling (SIR) algorithms. By setting up these values, a number of simulations using the health care system's data sets which contains the real RSSI measurements to evaluate the location error in term of various power levels and density nodes for all methods. Finally, we point out the effect of different power levels vs. different density nodes for the wireless patient tracking.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5C
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• pp.472-478
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• 2010

In the environment of wireless communication system of IEEE 802.15.3a UWB standard, the angle of arrival(AOA) estimation technique for the indoor wireless positioning algorithms, based on the AOA parameter estimation which fits well for the wireless communication channel and shows high estimation accuracy, is proposed. After the UWB signal model, based on the IEEE 802.1.3a standard, is constructed, the average weighted MUSIC technique is proposed, which shows better estimation accuracy than those of conventional estimation technique. Through the simulation studies, the environment of the indoor wireless positioning system including the IEEE 802.15.3a channel is configured and we demonstrate better estimation results by the proposed AOA estimation technique than those from the conventional method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.457-461
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• 2007

In many applications, received signal strength indicator is used for location tracking and sensor nodes localization. For location finding, the distances between sensor nodes can be estimated by converting received signal's power into distance using path loss prediction model. Many researches have done the analysis of power-distance relationship for radio channel characterization. In indoor environment, the general conclusion is the non-linear variation of RSSI values as distance varied linearly. This has been one of the difficulties for indoor localization. This paper presents works on indoor RSSI characterization based on statistical methods to find the overall trend of RSSI variation at different places and times within the same room From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. This two factors are directly indicated by the two main parameters of path loss prediction model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2243-2250
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• 2014

In wireless sensor networks(WSNs), geographical routing algorithms can enhance the network capacity. However, in real WSNs, it is difficult for each node to know its physical location accurately. Especially, indoor environments contain various obstacles such as concrete wall, furniture which cause non-line-of-sight(NLOS) conditions. To solve the problem, we propose location error compensation algorithm by using two difference topology constructions. First topology is based on mobile node's location which is obtained from anchor nodes. Second topology is based on mutual distance from neighbor nodes. The proposed algorithm efficiently detects and corrects the location errors and significantly enhances the network performance of geographic routing in the presence of location errors.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1158-1168
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• 2020

The distance vector-hop wireless sensor node location method is one of typical range-free location methods. In distance vector-hop location method, if a wireless node A can directly communicate with wireless sensor network nodes B and C at its communication range, the hop count from wireless sensor nodes A to B is considered to be the same as that form wireless sensor nodes A to C. However, the real distance between wireless sensor nodes A and B may be dissimilar to that between wireless sensor nodes A and C. Therefore, there may be a discrepancy between the real distance and the estimated hop count distance, and this will affect wireless sensor node location error of distance vector-hop method. To overcome this problem, it proposes a wireless sensor network node location method by modifying the method of distance estimation in the distance vector-hop method. Firstly, we set three different communication powers for each node. Different hop counts correspond to different communication powers; and so this makes the corresponding relationship between the real distance and hop count more accurate, and also reduces the distance error between the real and estimated distance in wireless sensor network. Secondly, distance difference between the estimated distance between wireless sensor network anchor nodes and their corresponding real distance is computed. The average value of distance errors that is computed in the second step is used to modify the estimated distance from the wireless sensor network anchor node to the unknown sensor node. The improved node location method has smaller node location error than the distance vector-hop algorithm and other improved location methods, which is proved by simulations.