• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.610-618
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• 2011

For improved localization around the indoor/outdoor transit area of buildings, this paper proposes an efficient algorithm combining the measurements from the WLAN (Wireless Local Area Network) and the GPS (Global Positioning System) for. The proposed hybrid localization algorithm considers both multipath errors and NLOS (Non-Line-of-Sight) errors, which occur in most wireless localization systems. To detect and isolate multipath errors occurring in GPS measurements, the propose algorithm utilizes conventional multipath test statistics. To convert WLAN signal strength measurements to range estimates in the presence of NLOS errors, a simple and effective calibration algorithm is designed to compute conversion parameters. By selecting and combining the reliable GPS and WLAN measurements, the proposed hybrid localization algorithm provides more accurate location estimates. An experiment result demonstrates the performance of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.119-124
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• 2013

Recent increasing demand on the indoor localization requires more advanced and hybrid technology. This paper proposes an application of the hybrid indoor localization method based on a position-coded pattern that can be used with other existing indoor localization techniques such as vision, beacon, or landmark technique. To reduce the pattern-recognition error rate, the error detection and correction algorithm was applied based on Hamming code. The indoor localization experiments based on the proposed algorithm were performed by using a QCIF-grade CMOS sensor and a position-coded pattern with an area of $1.7{\times}1.7mm^2$. The experiments have shown that the position recognition error ratio was less than 0.9 % with 0.4 mm localization accuracy. The results suggest that the proposed method could be feasibly applied for the localization of the indoor mobile service robots.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.2
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• pp.77-85
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• 2013

this study examined hybrid Time of Arrival/Angle of Arrival (TOA/AOA) localization technique in a cellular network. Based on the linearized equations from the TOA and AOA measurements, the weighted least square (WLS) method is proposed to obtain the location estimation of a mobile station (MS) by analyzing the statistical properties of the error vector in Line of Sight (LOS) and Non-line of Sight (NLOS) environments, respectively. Moreover, the precise expression of the Cramer-Rao lower bound (CRLB) for hybrid TOA/AOA measurements in different LOS/NLOS conditions was derived when the LOS error is a Gaussian variable and the NLOS error is an exponential variable. The idea of cooperative localization is proposed based on the additional information from short-range communication among the MSs in fourth generation (4G) cellular networks. Therefore, the proposed hybrid TOA/AOA WLS method can be improved further with the cooperative scheme. The simulation results show that the hybrid TOA/AOA method has better performance than the TOA only method, particularly when the AOA measurements are accurate. Moreover, the performance of the hybrid TOA/AOA method can be improved further by the cooperative scheme.

• Journal of Advanced Navigation Technology
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• v.12 no.5
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• pp.483-493
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• 2008

For effective wireless localization utilizing signal strength measurements based on IEEE 802.11 WLAN standard diversity of mobile hardware, characteristics of is one of the important problems to be considered for advanced location-based services. For improved accuracy regardless of a bias originating from the mobile hardware characteristics, this paper proposes a new localization algorithm, which is named as the hybrid Kriging algorithm. To evaluate the performance characteristics of the proposed algorithm, simulation and experiment results are illustrated. By the simulation and experiment result, the proposed algorithm is more accurate than the well-known location finger-print method given the same density of reference measurements.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.633-639
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• 2013

Several estimation methods used in the range measurement based wireless localization area have individual problems. These problems may not occur according to certain application areas. However, these problems may give rise to serious problems in particular applications. In this paper, three methods, ILS (Iterative Least Squares), DS (Direct Solution), and DSRM (Difference of Squared Range Measurements) methods are considered. Problems that can occur in these methods are defined and a simple hybrid solution is presented to solve them. The ILS method is the most frequently used method in wireless localization and has local minimum problems and a large computational burden compared with closed-form solutions. The DS method requires less processing time than the ILS method. However, a solution for this method may include a complex number caused by the relations between the location of reference nodes and range measurement errors. In the near-field region of the complex solution, large estimation errors occur. In the DSRM method, large measurement errors occur when the mobile node is far from the reference nodes due to the combination of range measurement error and range data. This creates the problem of large localization errors. In this paper, these problems are defined and a hybrid localization method is presented to avoid them by integrating the DS and DSRM methods. The defined problems are confirmed and the performance of the presented method is verified by a Monte-Carlo simulation.

• ETRI Journal
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• v.37 no.3
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• pp.533-540
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• 2015

In wireless localization, several linear closed-form solution (LCS) methods have been investigated as a direct result of the drawbacks that plague the existing iterative methods, such as the local minimum problem and heavy computational burden. Among the known LCS methods, both the direct solution method and the difference of squared range measurements method are considered in this paper. These LCS methods do not have any of the aforementioned problems that occur in the existing iterative methods. However, each LCS method does have its own individual error property. In this paper, a hybrid LCS method is presented to reduce these errors. The hybrid LCS method integrates the two aforementioned LCS methods by using two check points that give important information on the probability of occurrence of each LCS's individual error. The results of several Monte Carlo simulations show that the proposed method has a good performance. The solutions provided by the proposed method are accurate and reliable. The solutions do not have serious errors such as those that occur in the conventional standalone LCS and iterative methods.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3166-3181
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• 2012

Localization of mobile station (MS) has now gained considerable attention. Since the hybrid measurements can help to improve the positioning accuracy, several hybrid localization methods have been proposed in the literature. However, the high performance estimator with the closed-form solution and complete performance analysis for time-of-arrival/signal strength (TOA/SS) localization technique is still an opening issue. Two TOA/SS localization algorithms with the closed-form solutions are proposed for the cases with or without uncertainty in the positions of base stations. Furthermore, performance analysis for the TOA/SS localization technique is presented. Both the theoretical variances and Cramer-Rao lower bounds (CRLBs) are derived and the relationship between the cases with or without uncertainty is given. The paper also proves that the TOA/SS scheme has a lower CRLB than the TOA (or SS) scheme. Theoretical analysis and simulations show that the proposed method can reach its CRLB.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.36.5-36
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• 2001

Localization is one of the key problems in the navigation of autonomous mobile robots. The probabilistic Markov localization approaches offer a good mathematical framework to deal with the uncertainty of environment and sensor readings but their use for realtime applications is limited by their computational complexity. This paper aims to reduce the high computational cost associated with the probabilistic Markov localization algorithm. We propose a hybrid landmark-based localization method combining triangulation and probabilistic approaches, which can efficiently update position probability grid, while the probabilistic framework allows to make use of any available sensor data to refine robot´s belief about its current location. The simulation results show the effectiveness and robustness of the method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.05a
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• pp.30-31
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• 2018

The localization performance in the ship environment is degraded by RF interference due to steel structure characteristics and NLOS environment. In this paper, a wireless hybrid localization system using ZigBee, UWB, and LF technologies is proposed to improve position estimation accuracy in the ship environment.