• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1640-1651
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• 2017

To make an unmanned aerial vehicle (UAVs) fly in indoor environments, the indoor locations of the UAV are required. One of the approaches to calculate the locations of an UAV in indoor environments is enhanced trilateration using one Bluetooth-based beacon and three or more access points (APs). However, the locations of the UAV calculated by the common chord-based trilateration has errors due to the distance errors of the beacon measured at the multiple APs. This paper proposes a method that corrects the errors that occur in the process of applying the common chord-based trilateration to calculate the locations of an UAV. In the experiments, the results of measuring the locations using the proposed method in an indoor environment was compared and verified against the result of measuring the locations using the common chord-based trilateration. The proposed method improved the accuracy of location measurement by 81.2% compared to the common chord-based trilateration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2567-2586
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• 2012

Localization of sensor nodes is a key technology in Wireless Sensor Networks(WSNs). Trilateration is an important position determination strategy. To further improve the localization accuracy, a novel Trilateration based on Point In Triangle testing Localization (TPITL)algorithm is proposed in the paper. Unlike the traditional trilateration localization algorithm which randomly selects three neighbor anchors, the proposed TPITL algorithm selects three special neighbor anchors of the unknown node for trilateration. The three anchors construct the smallest anchor triangle which encloses the unknown node. To choose the optimized anchors, we propose Point In Triangle testing based on Distance(PITD) method, which applies the estimated distances for trilateration to reduce the PIT testing errors. Simulation results show that the PIT testing errors of PITD are much lower than Approximation PIT(APIT) method and the proposed TPITL algorithm significantly improves the localization accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.3 no.2
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• pp.18-31
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• 1985

The object of this study is to analize the trilateration adjustment by FEM. FEM is a numerical method for analysis dealing with problems of displacement and variation about the object. Since a plane trilateration net can be likend to a plan structural frame work in stress analysis, the technic of FEM can be used for trilateration adjustment Thus, this study applied FEM and Condition Equation Method to a trilateration adjustment, and investigated precision and characteristics of them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4B
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• pp.331-337
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• 2002

In this paper we propose extended Kalman filter (EKF)-trilateration method which associates EKF to conventional radiolocation technique, trilateration in order to improve the accuracy of dynamic orbit determination of geostationary satellite for broadcasting of highly accurate Standard Time/Frequency Signal (STFS). We then compare to analyze the time accuracies of three techniques which are differential mode, trilateration locating one of four calibrated earth stations on a neighboring country, and domestic-only baseline EKF-trilateration. Computer simulations have shown that in spite of domestic-only baseline EKF-trilateration of poor GDOP, it is possible to track and locate satellite with an accuracy of a few hundred meter which is the performance 10 times more accurate than trilateration can provide. Finally we can provide standard time service with the time accuracy better than a few ns (frequency stability : 10$\^$-14/ over 7 days) all around Korea peninsula.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.449-455
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• 2022

In this paper, we propose a position measuring system using trilateration based on the illuminance of a light-emitting diode (LED). Three LEDs are located on the ceiling of the virtual space, and each fixed coordinate is inputted to the monitoring program, and Length to the illuminance sensor is drawn through the relational expression of the length and illuminance value from the respective LED. Based on the derived length, the trilateration method is used to find object location information in virtual space. By using the least square equation to minimize the error of the length drawn to trilateration, the error is reduced to the utmost. Unlike the existing indoor positioning system using visible light communication (VLC), the proposed system does not require synchronization between the transmitter and the receiver, so the system can be configured simply.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.2
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• pp.35-43
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• 1990

In this paper a two dimensional network adjustment theory is developed to analyze the plane trilateration network of single triangle network, of quadrilateral network, of polygon trilateration network and of combined network. The characteristics of error were analysed by developing an error propagation equation for each form of plane trilateration network. In case of combined network, the result of error analysis was represented by error ellipses and gross error detection was carried out by data snooping method.

• The Journal of Korea Robotics Society
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• v.7 no.1
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• pp.45-56
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• 2012

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.65-67
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• 2021

This thesis is to proposer a new algorithm for a position measurement system using a trilateration method through visible light communication(VLC), by light emitting diode(LED). The length from each LED to the sensor is derived, and location information is found using trilateration method based on the derived length. Unlike th existing positioning system using visible light communication, the proposed positioning system is simpler and more cost effective because it does not require communication between the transmitter and the receiver.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.615-616
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• 2008

Generally, distance between sensor nodes is measured using received signal strength indicator (RSSI) in wireless sensor network (WSN). Since RSSI is not absolutely accurate and stable in indoor environment, the performance of position estimation largely depends on estimation methods. In this paper, performance evaluation is presented to compare trilateration based positioning technique and collaborative ranging (CR) technique. From evaluation results, CR method is shown to be better than trilateration based method in terms of accuracy and precision.

• Journal of Information Technology Applications and Management
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• v.15 no.2
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• pp.51-65
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• 2008

The purpose of this paper is introducing WiFi based EKF(Extended Kalman Filter) method for indoor positioning. The advantages of our EKF method include: 1) Any special equipment dedicated for positioning is not required. 2) implementation of EKF does not require off-line phase of fingerprinting methods. 3) The EKF effectively minimizes squared deviation of the trilateration method. In order to experimentally prove the advantages of our method, we implemented indoor positioning systems making use of the K-NN(K Nearest Neighbors), Bayesian, decision tree, trilateration, and our EKF methods. Our experimental results show that the average-errors of K-NN, Bayesian and decision tree methods are all close to 2.4 meters whereas the average errors of trilateration and EKF are 4.07 meters and 3.528 meters, respectively. That is, the accuracy of our EKF is a bit inferior to those of fingerprinting methods. Even so, our EKF is accurate enough to be used for practical indoor LBS systems. Moreover, our EKF is easier to implement than fingerprinting methods because it does not require off-line phase.