• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.217-227
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• 2022

In order to provide a location-based services regardless of indoor or outdoor space, it is important to provide position information of the terminal regardless of location. Among the wireless/mobile communication resources used for this purpose, Long Term Evolution (LTE) signal is a representative infrastructure that can overcome spatial limitations, but the positioning method based on the location of the base station has a disadvantage in that the accuracy is low. Therefore, a fingerprinting technique, which is a pattern recognition technology, has been widely used. The simplest yet widely applied algorithm among Fingerprint positioning technologies is k-Nearest Neighbors (kNN). However, in the kNN algorithm, it is difficult to find the optimal K value with the lowest positioning error for each location to be estimated, so it is generally fixed to an appropriate K value and used. Since the optimal K value cannot be applied to each estimated location, therefore, there is a problem in that the accuracy of the overall estimated location information is lowered. Considering this problem, this paper proposes a technique for adaptively varying the K value by using a Convolutional Neural Network (CNN) model among Artificial Neural Network (ANN) techniques. First, by using the signal information of the measured values obtained in the service area, an image is created according to the Physical Cell Identity (PCI) and Band combination, and an answer label for supervised learning is created. Then, the structure of the CNN is modeled to classify K values through the image information of the measurements. The performance of the proposed technique is verified based on actual data measured in the testbed. As a result, it can be seen that the proposed technique improves the positioning performance compared to using a fixed K value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3534-3553
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• 2021

The low cost of Bluetooth technology has led to its wide usage in indoor positioning. However, some inherent shortcomings of Bluetooth technology have limited its further development in indoor positioning, such as the unstable positioning state caused by the fluctuation of Received Signal Strength Indicator (RSSI) and the low transmission frequency accompanied by a poor real-time performance in positioning and tracking moving targets. To address these problems, an indoor fusion positioning algorithm of Bluetooth technology and pedestrian dead reckoning (PDR) based on a particle filter with dynamic adjustment of weights calculation strategy (BPDW) will be proposed. First, an orderly statistical filter (OSF) sorts the RSSI values of a period and then eliminates outliers to obtain relatively stable RSSI values. Next, the Group-based Trilateration algorithm (GTP) enhances positioning accuracy. Finally, the particle filter algorithm with dynamic adjustment of weight calculation strategy fuses the results of Bluetooth positing and PDR to improve the performance of positioning moving targets. To evaluate the performance of BPDW, we compared BPDW with other representative indoor positioning algorithms, including fingerprint positioning, trilateral positioning (TP), multilateral positioning (MP), Kalman filter, and strong tracking filter. The results showed that BPDW has the best positioning performance on static and moving targets in simulation and actual scenes.

• Journal of Positioning, Navigation, and Timing
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• v.5 no.3
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• pp.131-136
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• 2016

The present paper shows that beamforming algorithm such as Minimum Variance Distortionless Response (MVDR) based on array antenna signal processing can have not only anti-jamming but also anti-spoofing characteristics. A beam pattern due to the beamforming algorithm strengthens received signal power as it is formed in the incident direction of desired signal. During the process, the effect of unnecessary signals such as spoofing signals can be reduced because the beam pattern reduces received signal power in the incident directions excluding the beam pattern-directed direction. In order to analyze the anti-spoofing effect due to the beamforming algorithm, a software-based simulation environment was configured. An arbitrary error was applied between incident direction of Global Positioning System (GPS) satellite signal and steering vector direction of the beamforming algorithm to analyze the received signal power and required conditions were provided to see the anti-spoofing effect due to the beamforming algorithm. The used antenna was 7-element planar circular array and beam patterns were formed through the MVDR algorithm.

• Journal of Internet Computing and Services
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• v.2 no.5
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• pp.49-58
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• 2001

Mobile positioning measurement is the most important technology for Location Based Services in the cellular networks. Generally, we are expecting to use GPS to guarantee high accuracy of the mobile position, A CDMA network-based technique for the Mobile Station position calculation needs to be implemented in the cdma2000 network whether the handsets have GPS or not, The most reliable methods of the network-based location technologies are based on the estimation of time of signal traveling between MS and B18 in a network whose coordinates are identified, Other signal parameters such as the power of the received signal and the signal arrival direction cannot be used as main data for a location system because adoption of only the signal parameters will not meet the FCC requirements, In practice, the estimates of the time of signal propagation between MS and BTS always have errors resulting from low-resolution power of measurements and multi path signal propagation, This paper describes the combined network-based location technology in the cdma2000 1× necessary to meet US FCC requirements. The issues of a calibration table and statistic processing based on the pilot strength as well as combined network-based location technologies(TOA/ TDOA) will help to achieve higher location accuracy than specified in the US FCC Rule.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.75-83
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• 2024

In order to reduce the time and cost of developing a navigation system, a performance evaluation platform can be used. A User Interface (UI) is required to effectively evaluate the performance, which sets parameters and gives navigation sensor signals and data display, and also displays navigation results. In this paper, a LabVIEW-based UI design method for multi-integrated navigation systems is proposed and implementation results are presented. The UI consists of a signal and data generation part and a signal and data processing part. The signal and data generation part sets parameters for the signal and data generation and displays the navigation sensor signal and data generation results. The signal and data processing part sets parameters for the signal and data processing and displays the navigation results. The signal and data generation part and signal and data processing part are designed to satisfy the requirements of the UI for a performance evaluation of the navigation system. In order to show the usefulness of the proposed UI design method, parameters of the signal and data generation and the signal and data processing are set through the LabVIEW-based UI, and the Global Positioning System (GPS) signal and inertial measurement unit data generation results and the navigation results of a GPS Software Defined Receiver (SDR) and inertial navigation system are confirmed. The implementation results show that the proposed UI design method helps users conduct an effective performance evaluation of navigation systems.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.271-280
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• 2023

Pedestrian Dead Reckoning (PDR) methods using initial sensors are being studied to provide the location information of smart device users in indoor environments where satellite signals are not available. PDR can continuously estimate the location of a pedestrian regardless of the walking environment, but has the disadvantage of accumulating errors over time. Unlike this, WiFi signal-based wireless positioning technology does not accumulate errors over time, but can provide positioning information only where infrastructure is installed. It also shows different positioning performance depending on the environment. In this paper, an integrated positioning technology integrating two positioning techniques with different error characteristics is proposed. A technique for correcting the error of PDR was designed by using the location information obtained through WiFi Measurement-based fingerprinting as the measurement of Extended Kalman Filte (EKF). Here, a technique is used to variably calculate the error covariance of the filter measurements using the WiFi Fingerprinting DB and apply it to the filter. The performance of the proposed positioning technology is verified through an experiment. The error characteristics of the PDR and WiFi Fingerprinting techniques are analyzed through the experimental results. In addition, it is confirmed that the PDR error is effectively compensated by adaptively utilizing the WiFi signal to the environment through the EKF to which the adaptive error covariance proposed in this paper is applied.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.3
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• pp.97-105
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• 2015

A navigation signal based on orthogonal tiered polyphase code was proposed. For the proposed signal, tiered polyphase code was used as the code of a pilot channel. Tiered polyphase code is a complex number type code, and thus the pilot channel and data channel were separated using the Walsh code which makes the correlation between different codes become 0. The results of the simulation indicated that the correlation characteristics and signal acquisition performance of the proposed signal were identical to those of tiered polyphase code, and that the disadvantage of tiered polyphase code could be supplemented through a data channel in terms of signal tracking.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1059-1068
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• 2021

In urban areas, GPS(Global Positioning System)/GNSS(Global Navigation Satellite System) signals are blocked or distorted by structures such as buildings, which limits positioning. To compensate for this problem, in this paper, fingerprinting-based positioning using RSRP(: Reference Signal Received Power) information of LTE signals is performed. The W-KNN(Weighted - K Nearest Neighbors) technique, which is widely used in the positioning step of fingerprinting, yields different positioning performance results depending on the similarity distance calculation method and weighting method used in correlation. In this paper, the performance of the fingerprinting positioning according to the techniques used in correlation is comparatively analyzed experimentally.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.774-781
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• 2014

This paper presents a fingerprint database construction method for WLAN RSSI (Received Signal Strength Indicator)-based indoor positioning. When RSSI is used for indoor positioning, the fingerprint method can achieve more accurate positioning than trilateration and centroid methods. However, a FD (Fingerprint Database) must be constructed before positioning. This step is a very laborious process. To reduce the drawbacks of the fingerprint method, a radio propagation model-based FD construction method is presented. In this method, an FD can be constructed by a simulator. Experimental results show that the constructed FD-based positioning has a 3.17m (CEP) error. In this paper, a spatial correlation method is presented to estimate the NLOS(Non-Line of Sight) error included in the FD constructed by a simulator. As a result, the NLOS error of the FD is reduced and the performance of the error compensated FD-based positioning is improved. The experimental results show that the enhanced FD-based positioning has a 2.58m (CEP) error that is a reasonable performance for indoor LBS (Location Based Service).