• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.903-908
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• 2011

The purpose of this paper is to provider an indoor location measuring method, apparatus and Service available for mobile wireless network. This paper introduces positioning technology such as Basic Technology Element and QoS(Quality of Service) etc. of WPS(WiFi Positioning System) for mobile wireless network. An apparatus for sectionalizing an indoor area for indoor location measurement includes several steps. For example, a sector number input step, a sectionalization calculating step, a storing unit step etc. Also, This paper show advance Indoor positioning result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.2
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• pp.106-116
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• 2012

The huge success of location-aware applications has called for the rapid development of an alternative positioning system to the global positioning system (GPS) for indoor localization based on existing technologies, such as 802.11 wireless networks. This paper proposes the Wireless MAC Processor Positioning System (WMPS), which is a localization system running on off-the-shelf 802.11 Access Points and based on the time-of-flight ranging of users' standard terminals. This paper proves through extensive experiments that the propagation delays can be measured with the accuracy required by indoor applications despite the different noise components that can affect the result: latencies of the hardware transreceivers, multipath, ACK jitters and timer quantization. Key to this solution is the choice of the Wireless MAC Processor architecture, which enables a straightforward implementation of the ranging subsystem directly inside the commercial cards without affecting the basic DCF channel access algorithm. In addition to the proposed measurement framework, this study developed a simple and effective localization algorithm that can work without requiring any preliminary calibration or device characterization. Finally, the architecture allows the measurement methodology to be adjusted as a function of the network load or propagation environments at the run time, without requiring any firmware update.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.786-791
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• 2021

In this paper, in order to minimize limitations such as signal interference and positioning errors in existing indoor positioning systems, a smart LED-based positioning system for excellent line-of-sight radio environments and precise location tracking is proposed to improve accuracy. An IEEE 802.4 Zigbee module is mounted on the SMPS board of a smart LED; RSSI and LQI signals are received from a moving tag, and the system is configured to transmit the measured data to the positioning server through a gateway. For the experiment, the necessary hardware, such as the gateway and the smart LED module, were separately designed, and the experiment was conducted after configuring the system in an external field office. The positioning error was within 70cm as a result of performing complex calculations in the positioning server after transmitting a vector value of the moving object obtained from the direction sensor, together with a signal from the moving object received by the smart LED. The result is a significantly improved positioning error, compared to an existing short-range wireless communications-based system, and shows the level at which commercial products can be implemented.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.564-573
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• 2015

GPS is the representative positioning technology for providing the location information. This technique has the disadvantage that does not operate in the shadow areas, such as urban or dense forest and the interior. This paper proposes a hybrid indoor positioning algorithm, which estimates a more accurate location of the terminal using strength of the Wi-Fi signal from the indoor AP. To determine the location of the user, we establish the most appropriate path loss model for the measurement environment. by using the RSSI value measured in a variety of environment such as building structure, person, distance, etc. The path loss exponent obtained by the path loss model is changed according to the environment. REKF, PF estimate the position of the terminal by using measured value from the AP with path loss exponent. For more accurate position estimation, we select positioning system by the value of threshold measured by experiments rather than a single positioning system. Experimental results using the proposed hybrid algorithm show that the performance is improved by about 17% than the conventional single positioning method.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.789-797
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• 2006

A new method for the GPS repeater based indoor positioning is proposed and its feasibility is verified by experiments in previous paper. But the problems how can identify switching GPS repeater's ID and when switching will be occurred are remained. To solve the problem faced with, we propose the time synchronized switching GPS repeater and the methods of the detection of switching time and the estimation of TDOA. First, switching GPS repeater retransmits the signals synchronized on GPS time, sequentially. Always, first switching time is synchronized with 1 PPS. Second, we formulate the detection of switching time and the estimation of TDOA and propose the various methods. No method is existed absolutely superior to others in any conditions but the method is existed superior to others in specific condition. Finally, feasibility of indoor positioning using time-synchronized switching GPS repeater is evaluated through experiments in anechoic chamber and general environment with multipath.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.640-642
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• 2021

In order to collect a lot of data clearly and efficiently, it is essential to know the locations of the current facilities and analyze the movement data. The current location collection technology can collect data using a GPS (Global Positioning System) sensor, but in the case of GPS, it has strong straightness and low diffraction and reflectivity, making it difficult to position indoors. It is impossible to measure the distance between the server and the client because the signal sensitivity cannot be received. This paper implements an indoor positioning system using beacons and scanners in Raspberry Pi 3 B+. It controls Advertise Mode and Connection Mode at the same time using the scanner algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1139-1145
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• 2008

A robust position sensing system is proposed in this paper for a ubiquitous mobile robot which moves indoors as well as outdoors. The Differential GPS (DGPS) which has a position estimation error of less than 5 m is a general solution when the mobile robot is moving outdoor, while an active beacon system (ABS) with embedded ultrasonic sensors is reliable as an indoor positioning system. The switching from the outdoor to indoor or vice versa causes unstable measurements on account of the reference coordinates and algorithm changes. To minimize the switching time in the position estimation and to stabilize the measurement, a robust position sensing system is proposed. In the system, to minimize the switching delay, the door positions are stored and updated in a database. Using the database, the approaching status of the mobile robot from indoor to outdoor or vice versa has been checked and the switching conditions are prepared before the mobile robot actually moves out or moves into the door. The reliability and accuracy of the robust positioning system based on DGPS and ABS are verified and demonstrated through the real experiments using a mobile robot prepared for this research.

• Journal of Digital Contents Society
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• v.15 no.1
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• pp.129-136
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• 2014

Wi-Fi fingerprinting system is a very popular positioning method used in indoor spaces. The system depends on Wi-Fi Received Signal Strength (RSS) from Access Points (APs). However, the Wi-Fi RSS is changeable by multipath fading effect and interference due to walls, obstacles and people. Therefore, the Wi-Fi fingerprinting system produces low position accuracy. Also, Wi-Fi signals pass through walls. For this reason, the existing system cannot distinguish users' floor. To solve these problems, this paper proposes a LED fingerprinting system for accurate indoor positioning. The proposed system uses a received optical power from LEDs and LED-Identification (LED-ID) instead of the Wi-Fi RSS. In training phase, we record LED fingerprints in database at each place. In serving phase, we adopt a K-Nearest Neighbor (K-NN) algorithm for comparing existing data and new received data of users. We show that our technique performs in terms of CDF by computer simulation results. From simulation results, the proposed system shows that a positioning accuracy is improved by 8.6 % on average.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.