• ETRI Journal
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• v.35 no.6
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• pp.1084-1093
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• 2013

problem of pedestrian localization using mobile nodes containing impulse radio ultra wideband (IR-UWB) is considered. IEEE 802.15.4a-based IR-UWB can achieve accurate ranging. However, the coverage is as short as 30 m, owing to the restricted transmit power. This factor may cause a poor geometric relationship among the mobile nodes and anchor nodes in certain environments. To localize a group of pedestrians accurately, an enhanced cooperative localization method is proposed. We describe a sequential algorithm and define problems that may occur in the implementation of the algorithm. To solve these problems, a batch algorithm is proposed. The batch algorithm can be carried out after performing the sequential algorithm to linearize the nonlinear range equation. When a sequential algorithm cannot be performed due to a poor geometric relationship among nodes, a batch algorithm can be carried out directly. Herein, Monte Carlo simulations are presented to illustrate the proposed method and verify its performance.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.127-132
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• 2016

For a practical mobile robot team such as carrying out a search and rescue mission in a disaster area, the localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a global positioning system (GPS) is unavailable. The proposed architecture supports localizing robots seamlessly by finding their relative locations while moving from a global outdoor environment to a local indoor position. The proposed schemes use a cooperative positioning system (CPS) based on the two-way ranging (TWR) technique. In the proposed TWR-based CPS, each non-localized mobile robot act as tag, and finds its position using bilateral range measurements of all localized mobile robots. The localized mobile robots act as anchors, and support the localization of mobile robots in the GPS-shadow region such as an indoor environment. As a tag localizes its position with anchors, the position error of the anchor propagates to the tag, and the position error of the tag accumulates the position errors of the anchor. To minimize the effect of error propagation, this paper suggests the new scheme of full-mesh based CPS for improving the position accuracy. The proposed schemes assuring localization were validated through experiment results.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.141-147
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• 2017

In this paper, an efficient and robust localization algorithm using Receiver Signal Strength Difference (RSSD) for a non-cooperative RF emitter is given. The proposed algorithm firstly calculate the center point and radius of Apollonius's circles and then estimate the intersection point of the circles based on Time of Arrival concept. And this paper also compares the performance of RSSD localization algorithms such as Non-linear Least Squares and Linearized Least Squares by Lines of Position (LOP) with the proposed algorithm. And some conclusions have been reached regarding the relative accuracy, robustness and computational cost of these algorithms.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.255-261
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• 2007

We propose a optimal fusion method for localization of multiple robots utilizing correlation between GPS on each robot in common workspace. Each mobile robot in group collects position data from each odometer and GPS receiver and shares the position data with other robots. Then each robot utilizes position data of other robot for obtaining more precise estimation of own position. Because GPS data errors in common workspace have a close correlation, they contribute to improve localization accuracy of all robots in group. In this paper, we simulate proposed optimal fusion method of odometer and GPS through virtual robots and position data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1511-1519
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• 2010

In this paper, we proposed and analyzed a RSSI based cooperative localization algorithm considering wireless propagation characteristics in indoor and outdoor environments for wireless sensor networks, which can estimate the BN position. The conventional RSSI based estimation scheme has low precision ranging due to instability propagation characteristics by time variable. Hence, we implemented ray-launching simulator for analysis of propagation characteristics in 4 case, and experimented proposed localization scheme with 4 RN and 1 to 5 BN. Simulation results show that NLCA has estimation error as 2m-3.5m, however, proposed CLA/ECLA has 1.3m-2.5m/0.5m-1.2m by same environments. Therefore, if we can consider channel characteristics, the proposed algorithm provides higher localization accuracy than RSSI based conventional one.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.725-730
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• 2012

In this paper, we propose the localization algorithm for the cooperative behavior of the swarm robots based on WSN (Wireless Sensor Network). The proposed method is as follows: First, we measure positions of the L-bot (Leader robot) and F-bots (Follower robots) by using the APIT (Approximate Point In Triangle) and the RSSI (Received Signal Strength Indication). Second, we measure relative positions of the F-bots against the pre-measured position of the L-bot by using trilateration. Then, to revise a position error caused by noise of the wireless signal, we use the particle filter. Finally, we show the effectiveness and feasibility of the proposed method though some simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.296-301
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• 2011

This paper deals with the simultaneous localization and mapping system using cooperative robot. For recognizing environment, swarm robot uses the ultrasonic sensors and vision sensor. Ultrasonic sensors measure the distance information, and vision sensor recognizes the predefined landmark. we used SURF with excellent quality and fast matching in order to recognize landmark. Due to measurement error of sensors, we fusion them using particle filter for accurate localization and mapping. Finally, we show the feasibility of the proposed method through some experiments.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.677-683
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• 2009

In this study, we designed and implemented testbed for localization algorithm by using a area reduction method in outdoor environment. The proposed algorithm used 3 steps of area reduction method, which estimated blind nodes position. Also, we have experimented with using a Zigbee module for 5 fixed reference nodes and 4 blind nodes in sensor field of $60m{\times}23m$. The results show that our algorithm is improved the localization accuracy even at the number of ref. node is fixed and the number of blind node is increased. In future research, we will be adding the function of seamless localization in indoor and NLOS(non-line of sight) environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1603-1623
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• 2020

Multiple Mobile Robots System (MMRS) has shown many attractive features in lots of real-world applications that motivate their rapid and wide diffusion. In MMRS, the Cooperative Localization (CL) is the basis and premise of its high-performance task. However, the statistical characteristics of the system noise should be already known in traditional CL algorithms, which is difficult to satisfy in actual MMRS because of the numerous of disturbances form the complex external environment. So the CL accuracy will be reduced. To solve this problem, an improved Adaptive Active Cooperative Localization (A²CL) algorithm based on information optimization strategy for MMRS is proposed in this manuscript. In this manuscript, an adaptive information fusion algorithm based on the variance component estimation under Extended Kalman filter (VCEKF) method for MMRS is introduced firstly to enhance the robustness and accuracy of information fusion by estimating the covariance matrix of the system noise or observation noise in real time. Besides, to decrease the effect of observation uncertainty on CL accuracy further, an observation optimization strategy based on information theory, the Model Predictive Control (MPC) strategy, is used here to maximize the information amount from observations. And semi-physical simulation experiments were carried out to verity the A²CL algorithm's performance finally. Results proved that the presented A²CL algorithm based on information optimization strategy for MMRS cannot only enhance the CL accuracy effectively but also have good robustness.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.1-10
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• 2011

The spectrum sensing is one of the fundamental functions to realize the cognitive radios. One of problems in the spectrum sensing is that the performance of spectrum sensing can be degraded due to fading and shadowing. In order to overcome the problem, cooperative spectrum sensing method is proposed, which uses a distributed detection model and can increase sensing performance. However, the performance of cooperative spectrum sensing can be still affected by the interference factors such as obstacle and malicious user. Especially, most of cooperative spectrum sensing methods only considered the stationary primary user. In the ubiquitous environment, however the mobile primary users should be considered. In order to overcome the aforementioned problem, in this paper we propose a robust spectrum detection method based on localization where we estimate the location of the mobile primary user, and then based on the location and transmission range of primary user we detect interference users if there are, and then the local sensing reporting from detected interference users are excluded in the decision fusion process. Through simulation, it is shown that the sensing performance of the proposed scheme is more accurate than that of conventional other schemes