• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.819-824
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• 2017

This paper presents a target localization scheme for distributed Multi-input Multi-output(MIMO) radar system using ToA measurements obtained from multiple transmitter and receiver pairs. The proposed method can locate the target from an arbitrary initial point by iteratively finding the Taylor linear approximation equation. The simulation results show that proposed method achieves the better mean square error(MSE) performance than the existing target localization methods, and furthermore, attains Cramer-Rao Lower Bound(CRLB).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.814-821
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• 2009

In an ultrawide band (UWB) indoor wireless localization, time of arrival (TOA) parameter estimation techniques have some difficulties in acquiring a reasonable TOA estimate because of the clustered multipath components overlapping or random time intervals mainly due to non line-of-sight (NLOS) environment. In order to solve that problem and achieve an excellent UWB indoor wireless localization, we propose a UWB signal model and a robust TOA parameter estimation technique that has little effect on the clustered problems unlike the conventional technique. Through simulation studies, the validity of the proposed model and the TOA estimation technique are examined. The performance of estimation error is also analyzed.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.186-196
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• 2010

In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.1059-1066
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• 2011

This paper makes a close inquiry into ill-conditioning that may be occurred in wireless localization of the sensor nodes based on network signals in the wireless sensor network and provides the clue for solving the problem. In order to estimate the location of a node based on the range information calculated using the signal propagation time, LS (Least Squares) method is usually used. The LS method estimates the solution that makes the squared estimation error minimal. When a nonlinear function is used for the wireless localization, ILS (Iterative Least Squares) method is used. The ILS method process the LS method iteratively after linearizing the nonlinear function at the initial nominal point. This method, however, has a problem that the final solution may converge into a LM (Local Minimum) instead of a GM (Global Minimum) according to the deployment of the fixed nodes and the initial nominal point. The conditions that cause the problem are explained and an adaptive method is presented to solve it, in this paper. It can be expected that the stable location solution can be provided in implementation of the wireless localization methods based on the results of this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1044-1050
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• 2014

Robots used for pipe inspection have been studied for a long time and many mobile mechanisms have been proposed to achieve inspection tasks within pipelines. Localization is an important factor for an inpipe robot to perform successful autonomous operation. However, sensors such as GPS and beacons cannot be used because of the unique characteristics of inpipe conditions. In this paper, an inpipe localization algorithm based on elbow detection is presented. By processing the projected marker images of laser pointers and the attitude and heading data from an IMU, the odometer module of the robot determines whether the robot is within a straight pipe or an elbow and minimizes the integration error in the orientation. In addition, an off-line positioning algorithm has been performed with forward and backward estimation and Procrustes analysis. The experimental environment has consisted of several straight pipes and elbows, and a map of the pipeline has been constructed as the result.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.12
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• pp.52-60
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• 2010

Knowledge of the physical locations of access point of WLAN is becoming increasingly important with the rise of location-based services. In this article, we propose a new AP localization method using neural network approach. Basic theory and properties are derived for precise outdoor AP localization using GPS location information and RSSI. Rules for neural network model are derived and simulation has finally been done to demonstrate the efficiency of the proposed method. The simulation results show that the proposed method can result in AP localization with very. low error probability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.570-577
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• 2014

Range-based real time localization systems require superior localization techniques as well as accurate ranging algorithms for better performance. To evaluate the ranging accuracy between two nodes in practical environments, this paper does not only present a qualitative analysis by computing a distance equation under SDS-TWR measurement model of no symmetry assumption, but also executes a quantitative evaluation by doing experiments after building up a test network employing the developed sensor node. Experimental results show that the ranging accuracy of the proposed implementation of IEEE 802.15.4a software stack is superior with smaller average error rate by 60% to one of the commercial Nanotron's reference development kit.

• 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 Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.157-164
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• 2014

The accuracy of instantaneous passive emitter localization varies with sensing platforms and measurable parameters. Appropriate combination of instantaneous measurable parameters have more accurate localization performance than a single parameter based localization in general. Emitter localization is preferred to use a small number of receivers as possible for the efficiency of strategic management in the field of modern electronic warfare support. For this reason, we compare CRLB (Cramer-Rao lower bound) of two moving platform with various measurable parameters to search a appropriate choice of parameters for the better localization performance through the x-y axis CEP (circular error probable) derived form CLRB. In addition, we present the relation of the localization performance and accuracy of measurable parameters.