• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.206-221
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• 2019

Source localization in three-dimensional (3-D) wireless sensor networks (WSNs) is becoming a major research focus. Due to the complicated air-ground environments in 3-D positioning, many of the traditional localization methods, such as received signal strength (RSS) may have relatively poor accuracy performance. Benefit from prior learning mechanisms, fingerprinting-based localization methods are less sensitive to complex conditions and can provide relatively accurate localization performance. However, fingerprinting-based methods require training data at each grid point for constructing the fingerprint database, the overhead of which is very high, particularly for 3-D localization. Also, some of measured data may be unavailable due to the interference of a complicated environment. In this paper, we propose an efficient kernel based 3-D localization algorithm via tensor completion. We first exploit the spatial correlation of the RSS data and demonstrate the low rank property of the RSS data matrix. Based on this, a new training scheme is proposed that uses tensor completion to recover the missing data of the fingerprint database. Finally, we propose a kernel based learning technique in the matching phase to improve the sensitivity and accuracy in the final source position estimation. Simulation results show that our new method can effectively eliminate the impairment caused by incomplete sensing data to improve the localization performance.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.55-62
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• 2016

In this paper, we present indoor positioning technologies using the wireless signal categorizing them into triangulation based, fingerprinting based, and cell ID based technologies. We describe several representative techniques for each of them emphasizing their strengths and weaknesses. We define important performance issues for indoor positioning technologies and analyze recent technologies according to the performance issues. We believe that this paper provide wise view and necessary information for recent indoor positioning technologies using wireless signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9C
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• pp.573-580
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• 2011

WSNs (Wireless Sensor Networks) are becoming more widely used in various fields, and improving localization performance is a crucial and essential issue for sensor network applications. In this paper, we propose a low-complexity localization mechanism for WSNs that operates in 3D (Three-Dimensional) space. The basic idea is to use aerial vehicles or flying objects that are deliberately equipped with the anchor nodes. These anchor nodes periodically broadcast beacon signals containing their current locations, and the unknown nodes receive these signals as soon as they enter the communication range of the anchors. We estimate the locations of the unknown nodes based on the proposed scheme that transforms the 3D problem into 2D computations to reduce the complexity of 3D localization. Simulated results show that our approach is an effective scheme for 3D self-positioning in WSNs.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.81-86
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• 2013

In this paper, the parameter identification for localization scheme for the optics-based micro sensor node is conducted. We analyzed short measurement range problem which can be occurred in optical based micro sensor node localization method using a time of flight. And we set up the theory for distance and maximum reflected laser power to overcome the problem by identifying hardware parameters like laser power, effective area of MEMS CCR, sensitivity of photodetector, and so on. Experimental results of measurement of maximum reflected laser power were compared with results of the theory. By using the theory, we can identify hardware parameters of localization scheme to measure particular position of the optics-based micro sensor node.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.197-203
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• 2010

The problem of location awareness in wireless sensor networks where nodes use GPS (Global Positioning System), remains challenging problem, when considering the required large energy consumption during the localization phase. In this paper we designed hardware for GPS based localization and propose a framework, called ELS, to consume low cost energy. In the ELS framework, sensor nodes are equipped with GPS. Because GPS spends large energy for position awareness, conventional localization algorithms cannot use GPS-device. We try to find a solution for efficient energy expenditure of GPS. Finally, we derive optimal transmission power of GPS data and a scheme of localization through experiment and simulation.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.283-285
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• 2005

If the ubiquitous computing times come before long, Context Awareness will be prominent among improved computing functions which are serviced to user. It is the very sense network, new technology, that makes it possible to recognize circumstances.In a lot of research projects about sensor network, this paper proposes the efficient method of localization for sensor network. I propose the possibility of localization using wireless RSS with no modification of hardware for sensor node and then suggest the limitation factors of method for efficiently improving performance.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.883-887
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• 2011

Location-based service (LBS) is becoming an important part of the information technology (IT) business. Localization is a core technology for LBS because LBS is based on the position of each device or user. In case of outdoor, GPS - which is used to determine the position of a moving user - is the dominant technology. As satellite signal cannot reach indoor, GPS cannot be used in indoor environment. Therefore, research and study about indoor localization technology, which has the same accuracy as an outdoor GPS, is needed for "seamless LBS". For indoor localization, we consider the IEEE802.11 WLAN environment. Generally, received signal strength indicator (RSSI) is used to obtain a specific position of the user under the WLAN environment. RSSI has a characteristic that is decreased over distance. To use RSSI at indoor localization, a mathematical model of RSSI, which reflects its characteristic, is used. However, this RSSI of the mathematical model is different from a real RSSI, which, in reality, has a sensitive parameter that is much affected by the propagation environment. This difference causes the occurrence of localization error. Thus, it is necessary to set a proper RSSI model in order to obtain an accurate localization result. We propose a method in which the parameters of the propagation environment are determined using only RSSI measurements obtained during localization.

• Journal of Ocean Engineering and Technology
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• v.31 no.2
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• pp.170-176
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• 2017

In this paper, we propose an underwater localization scheme through the fusion of an inertial navigation system (INS) and the received signal strength (RSS) of electromagnetic (EM) wave sensors to guarantee precise localization performance with high sampling rates. In this localization scheme, the INS predicts the pose of the unmanned underwater vehicle (UUV) by dead reckoning at every step, and the RF sensors corrects the UUV position functions using the Earth-fixed reference when the UUV is located in underwater wireless sensor networks (UWSN). The localization scheme and state modeling were conducted in the extended Kalman filter framework, and UUV localization experiments were conducted in a basin environment. The scheme achieved reliable localization accuracy during long-term navigation, demonstrating the feasibility of exploiting EM wave attenuation as Earth-fixed reference sensors.

• Digital Contents Society Review
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• v.3 no.1
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• pp.39-45
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• 2007

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.409-414
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• 2010

The applications based on geographical location are increasing rapidly in wireless sensor networks (WSN). Recently, various localization algorithms have been proposed but the majority of algorithms rely on the specific hardware to measure the distance from the signal sources. In this paper, we propose the Weighted Multiple Rings Localization(WMRL). We assume that each deployed anchor node may periodically emit the successive beacon signals of the different power level. Then, the beacon signals form the concentric rings depending on their emitted power level, theoretically. The proposed algorithm defines the different weighting factor based on the ratio of each radius of ring. Also, If a sensor node may listen, it can find the innermost ring of the propagated signal for each anchor node. Based on this information, the location of a sensor node is derived by a weighted sum of coordinates of the surrounding anchor nodes. Our proposed algorithm is fully distributed and does not require any additional hardwares and the unreliable distance indications such as RSSI and LQI. Nevertheless, the simulation results show that the WMRL with two rings twice outperforms centroid algorithm. In the case of WMRL with three rings, the accuracy is approximately equal to WCL(Weighted Centroid Localization).