• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.15-21
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• 2011

In the range-based localization, the localization accuracy will be high dependent on the accuracy of distance measurement between two nodes. The received signal strength(RSS) is one of the simplest methods of distance measurement, and can be easily implemented in a ranging-based method. However, a RSS-based localization scheme has few problems. One problem is that the signal in the communication channel is affected by many factors such as fading, shadowing, obstacle, and etc, which makes the error of distance measurement occur and the localization accuracy of sensor node be low. The other problem is that the sensor node estimates its location for itself in most cases of the RSS-based localization schemes, which makes the sensor network life time be reduced due to the battery limit of sensor nodes. Since beacon nodes usually have more resources than sensor nodes in terms of computation ability and battery, the beacon node based localization scheme can expand the life time of the sensor network. In this paper, therefore we propose a beacon node based localization algorithm using received signal strength(RSS) and path loss calibration in order to overcome the aforementioned problems. Through simulations, we prove the efficiency of the proposed scheme.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.436-442
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• 2015

In this paper, we develop an indoor localization device which embeds localization information into indoor light-emitting-diodes (LED) lighting systems. The key idea of our device is the use of the newly proposed "bit stuffing method". Through the use of stuff bits, our device is able to measure signal strengths even in transient states, which prohibits interference between lighting signals. The stuff bits also scatter the parts of the signal where the LED is turned on, thus provides quality indoor lighting. Additionally, for the indoor localization system based on RSSI and TDM to be practical, we propose methods for the control of LED lamps and compensation of received signals. The effectiveness of the proposed scheme is validated through experiments with a low-cost implementation including an indoor navigation task.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.368-373
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• 2010

A new indoor mobile robot localization method is presented. Robot recognizes well designed single color landmarks on the ceiling by vision system, as reference to compute its precise position. The proposed likelihood prediction based method enables the robot to estimate its position based only on the orientation of landmark.The use of single color landmarks helps to reduce the complexity of the landmark structure and makes it easily detectable. Edge based optical flow is further used to compensate for some landmark recognition error. This technique is applicable for navigation in an unlimited sized indoor space. Prediction scheme and localization algorithm are proposed, and edge based optical flow and data fusing are presented. Experimental results show that the proposed method provides accurate estimation of the robot position with a localization error within a range of 5 cm and directional error less than 4 degrees.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.774-783
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• 2020

For the issue of subsurface target localization by reverse projection, a new approach of target localization with different distances based on symmetric sub-array multiple-input multiple-output (MIMO) radar is proposed in this paper. By utilizing the particularity of structure of the two symmetric sub-arrays, the received signals are jointly reconstructed to eliminate the distance information from the steering vectors. The distance-independent direction of arrival (DOA) estimates are acquired, and the localizations of subsurface targets with different distances are realized by reverse projection. According to the localization mechanism and application characteristics of the proposed algorithm, the grid zooming method based on spatial segmentation is used to optimize the locaiton efficiency. Simulation results demonstrate the effectiveness of the proposed localization method and optimization scheme.

• Journal of the Society of Disaster Information
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• v.14 no.3
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• pp.315-324
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• 2018

Purpose: This paper propose a temporary indoor positioning scheme with devices of internet of things (IoT) for disastrous situations in places without the infrastructure of networks. Method: The proposed scheme is based on the weighted centroid localization scheme that can estimate the position of a target with simple computation. Results: It also is implemented with the IoT devices at the underground parking lot, where the network is not installed, of general office building. According to the experiment results, the positioning error was around 10m without a priori calibration process at $82.5m{\times}56.4m$ underground space. Conclusion: The proposed scheme can be deployed many places without the infrastructure of networks, such as parking lots, warehouses, factory, etc.

• 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 Korea Multimedia Society
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• v.5 no.1
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• pp.18-27
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• 2002

A hierarchical representation scheme for planar curves, MBO-tree, is proposed in this paper, which provides natural approximation and efficient localization. MBO-tree is based on the Douglas-Peucker algorithm (iterative end-point fit algorithm), but approximation errors that are stored with corresponding points in MBO-tree nodes and are used for abstraction measures are adjusted by force to eliminate unnatural approximation. The error adjusting is just making the approximation error of a node in a MBO-tree to be less than or equal to that of its parent. In point of localization, the bounding area of a curve is represented with a minimum bounding octangle (MBO), which can enclose the curve more compactly compared with those of other hierarchical schemes, such as the strip tree, the arc tree and the HAL tree. The MBO satisfies the hierarchical inclusion property that is useful for hierarchical geometrical operations, such as the point-inclusion test and the polygon intersection test. Through several experiments, we found that the proposed scheme was able to approximate more naturally and to localize more effectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1486-1495
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• 2018

This paper investigates the autonomous ground vehicle (AGV) localization filter design problem under GNSS-denied environments. It is assumed that the given landmarks do not have unique features due to the lack of a prior knowledge on them. For such case, the AGV may have difficulties in distinguishing the position measurement of the detected landmark from those of other landmarks with the same feature, hence the conventional localization filters are not applicable. To resolve this technical issue, the localization filter design problem is formulated as a special form of the data association determining whether the detected feature is actually originated from which landmark. The measurement hypotheses generated by landmarks with the same feature are evaluated by the nearest neighbor data association scheme to reduce the computational burden. The position measurement corresponding to the landmark with the most probable hypothesis is used for localization filter. Through the experiments in real-driving condition, it is shown that the proposed method provides satisfactory localization performance in spite of using non-unique landmarks.

• Journal of the Korean Society of Industry Convergence
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• v.10 no.2
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• pp.105-113
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• 2007

Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of application. Sensor position is used for its data to be meaningful and for energy efficient data routing algorithm especially geographic routing. The previous works for sensor localization utilize global positioning system(GPS) or estimate unknown-location nodes position with help of some small reference nodes which know their position previously. However, the traditional localization techniques are not well suited in the senor network for the cost of sensors is too high. In this paper, we propose the sensor localization method with a mobile robot, which knows its position, moves through the sensing field along pre-scheduled path and gives position information to the unknown-location nodes through wireless channel to estimate their position. We suggest using the sensor position estimation method and an efficient mobility path model. To validate our method, we carried out a computer simulation, and observed that our technique achieved sensor localization more accurately and efficiently than the conventional one.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.996-1001
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• 2005

Recently, with the development of service robots and with the new concept of ubiquitous world, the position estimation of mobile objects has been raised to an important problem. As pre-liminary research results, some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed in this paper. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter: 1. The RFID receiver gets the synchronization signal from the mobile robot and 2. The ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from. Three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can get the ultrasonic signals from only one or two beacons, because of the obstacles located along the moving path. Therefore, in this paper, as one of our dedicated contribution, the position estimation scheme with less than three sensors has been developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.