scholarly journals A Network-based Positioning Method to Locate False Base Stations

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Leyli Karacay ◽  
Zeki Bilgin ◽  
Ayse Bilge Gunduz ◽  
Pinar Comak ◽  
Emrah Tomur ◽  
...  
Keyword(s):  
Base Stations ◽  
Positioning Method

scholarly journals Application of LSTM Network to Improve Indoor Positioning Accuracy

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5824
Author(s):  
Dongqi Gao ◽  
Xiangye Zeng ◽  
Jingyi Wang ◽  
Yanmang Su
Keyword(s):  
Short Term Memory ◽  
Indoor Positioning ◽  
Base Stations ◽  
Ultra Wideband ◽  
Positioning Accuracy ◽  
Last Mile ◽  
Ranging Error ◽  
Positioning Method ◽  
Lstm Network ◽  
Positioning Algorithm

Various indoor positioning methods have been developed to solve the “last mile on Earth”. Ultra-wideband positioning technology stands out among all indoor positioning methods due to its unique communication mechanism and has a broad application prospect. Under non-line-of-sight (NLOS) conditions, the accuracy of this positioning method is greatly affected. Unlike traditional inspection and rejection of NLOS signals, all base stations are involved in positioning to improve positioning accuracy. In this paper, a Long Short-Term Memory (LSTM) network is used while maximizing the use of positioning equipment. The LSTM network is applied to process the raw Channel Impulse Response (CIR) to calculate the ranging error, and combined with the improved positioning algorithm to improve the positioning accuracy. It has been verified that the accuracy of the predicted ranging error is up to centimeter level. Using this prediction for the positioning algorithm, the average positioning accuracy improved by about 62%.

The Kalman Positioning Algorithm Based on TDOA/AOA

2013 ◽  
Vol 739 ◽  
pp. 602-607
Author(s):  
Zhong Liang Deng ◽  
Xiao Guan Wang
Keyword(s):  
Kalman Filter ◽  
Optimal Control Problems ◽  
Base Stations ◽  
Control Problems ◽  
Optimal Filtering ◽  
Hybrid Positioning ◽  
Positioning Method ◽  
Kalman Filter Algorithm ◽  
Positioning Algorithm ◽  
Positioning Time

TDOA is a common used positioning method. Its advantage is to overcome the disadvantage that positioning time reference is strictly required in TOA method, and the measurement method is relatively simple. AOA needs only two base stations to realise positioning in theory, but the positioning accuracy is lower. TDOA/AOA hybrid positioning algorithm can certainly overcome this limitation to realize high precision positioning. Kalman filter is an optimum regression data processing algorithm. It is applicated widely in various optimal filtering and optimal control problems. For most of the problems, it is optimal, the most efficient and even the most useful. In this article Kalman filter algorithm is utilized to estimate the value of TDOA and AOA, which is used for position calculating to improve the accuracy of positioning.

scholarly journals iBeacon Indoor Positioning Method Combined with Real-Time Anomaly Rate to Determine Weight Matrix

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 120
Author(s):  
Yu Guo ◽  
Jiazhu Zheng ◽  
Weizhu Zhu ◽  
Guiqiu Xiang ◽  
Shaoning Di
Keyword(s):  
Anomaly Detection ◽  
Indoor Positioning ◽  
Weight Matrix ◽  
Base Stations ◽  
Signal Source ◽  
Received Signal Strength Indicator ◽  
Abnormal Signal ◽  
Positioning Method ◽  
Lm Algorithm ◽  
Isolation Forest

This paper proposes an indoor positioning method based on iBeacon technology that combines anomaly detection and a weighted Levenberg-Marquadt (LM) algorithm. The proposed solution uses the isolation forest algorithm for anomaly detection on the collected Received Signal Strength Indicator (RSSI) data from different iBeacon base stations, and calculates the anomaly rate of each signal source while eliminating abnormal signals. Then, a weight matrix is set by using each anomaly ratio and the RSSI value after eliminating the abnormal signal. Finally, the constructed weight matrix and the weighted LM algorithm are combined to solve the positioning coordinates. An Android smartphone was used to verify the positioning method proposed in this paper in an indoor scene. This experimental scenario revealed an average positioning error of 1.540 m and a root mean square error (RMSE) of 1.748 m. A large majority (85.71%) of the positioning point errors were less than 3 m. Furthermore, the RMSE of the method proposed in this paper was, respectively, 38.69%, 36.60%, and 29.52% lower than the RMSE of three other methods used for comparison. The experimental results show that the iBeacon-based indoor positioning method proposed in this paper can improve the precision of indoor positioning and has strong practicability.

scholarly journals A Mobile Positioning Method Based on Deep Learning Techniques

Electronics ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 59 ◽  
Author(s):  
Ling Wu ◽  
Chi-Hua Chen ◽  
Qishan Zhang
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Time Series Data ◽  
Location Estimation ◽  
Base Stations ◽  
Series Data ◽  
Average Error ◽  
Mobile Positioning ◽  
Learning Techniques ◽  
Positioning Method

This study proposes a mobile positioning method that adopts recurrent neural network algorithms to analyze the received signal strength indications from heterogeneous networks (e.g., cellular networks and Wi-Fi networks) for estimating the locations of mobile stations. The recurrent neural networks with multiple consecutive timestamps can be applied to extract the features of time series data for the improvement of location estimation. In practical experimental environments, there are 4525 records, 59 different base stations, and 582 different Wi-Fi access points detected in Fuzhou University in China. The lower location errors can be obtained by the recurrent neural networks with multiple consecutive timestamps (e.g., two timestamps and three timestamps); from the experimental results, it can be observed that the average error of location estimation was 9.19 m by the proposed mobile positioning method with two timestamps.

scholarly journals An Improved Positioning Method for Two Base Stations in AIS

Sensors ◽  
2018 ◽  
Vol 18 (4) ◽  
pp. 991 ◽  
Author(s):  
◽  
◽  
Keyword(s):  
Base Stations ◽  
Positioning Method

Implementation of Location-Based Security Services

2020 ◽  
pp. 100-104
Author(s):  
M.V. Kostenko ◽  
O.A. Galenchikova
Keyword(s):  
Wide Band ◽  
Conveyor Belt ◽  
Base Stations ◽  
Belt Conveyor ◽  
Distance Measurements ◽  
Security Services ◽  
Local Positioning System ◽  
Positioning Method ◽  
A Site ◽  
Band Signal

The paper discusses the feasibility of implementing a system to prevent personnel from riding a conveyor. This system is based on the data collected by the local positioning system applying the method of distance measurements by the travel time of the ultra-wide band signal. Tests were performed using the SBGPS system produced by Granch Ltd. (Novosibirsk), deployed at the coal mine, for which a site was selected equipped with a belt conveyor and one of the base stations, that supports the tested positioning method. The results demonstrate that the accuracy of this system allows an easy differentiation between the movement of the controlled objects on foot and on top of the conveyor belt. The reaction time of the system is about 5-7 seconds with a stable wireless connection, which requires considering the area of the controlled device relocation as well as possible constraints on deployment of the base stations, i.e. additional requirements for areas with this functionality when deploying the infrastructure.

Developing GIS portal to ensure sanitary and epidemiological surveillance of transferring radio engineering objects

2020 ◽  
Vol 99 (4) ◽  
pp. 344-350
Author(s):  
Evgeny V. Zibarev ◽  
A. S. Afanasev ◽  
O. V. Slusareva ◽  
T. I. Muragimov ◽  
V. A. Stepanets ◽  
...  
Keyword(s):  
Electromagnetic Fields ◽  
Analytical Data ◽  
Base Stations ◽  
Epidemiological Surveillance ◽  
Graphical Form ◽  
Residential Areas ◽  
Information Portal ◽  
Radiofrequency Electromagnetic Fields ◽  
Online Mode ◽  
Automated Processes

In recent years, in the Russian Federation there has been an increase in the levels of radiofrequency electromagnetic fields in residential areas, including due to an increase in the number of base stations (BS). The purpose of sanitary and epidemiological surveillance at the stages of placement and commissioning of base stations (BS) is to prevent their adverse effects on public health. The increase in the number of base stations, together with the advent of new electronic equipment and antennas, provide opportunities for improving the processes of their accounting at the stage of placement and monitoring of the levels of radiofrequency electromagnetic fields at the operation stage. This automation tool can be a geo-information portal for providing sanitary and epidemiological surveillance of cellular base stations. The prototype of the geo-information portal allows both calculating the size of sanitary protection zones (SPZ) and building restriction zones (RZ) from the BS in online mode, displaying the results of calculations in graphical form and issuing sanitary and epidemiological conclusions for the placement and operation of base stations. The geo-information portal has the ability to synchronize with the data of the radio frequency center. Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing will be able to receive up-to-date analytical data. There will be completely automated processes of collecting, processing and storing information on BS.

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