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A simple iterative positioning algorithm for client node localization in WLANs

EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2013年第1期2013卷 1页

作者： Trevisan, Luis M. Pellenz, Marcelo E. Penna, Manoel C. Souza, Richard D. Fonseca, Mauro S. P. Pontifical Catholic Univ Parana PUCPR BR-1155 Curitiba Parana Brazil Fed Univ Technol Parana UTFPR BR-3165 Curitiba Parana Brazil

The ability to determine in real-time the geographic location of client nodes is an important tool in wireless networks, allowing instantaneous mobile tracking, implementation of location-aware services and also efficient channel and power allocation planning. Among existing classical cooperative localization techniques for wireless networks, the maximum likelihood estimator (MLE) is theoretically the best. However, the gradient-based algorithms that are commonly used for maximum likelihood estimation are quite sensitive to the initial values and cannot achieve the theoretical optimal performance. In this paper, we propose a new iterative positioning algorithm based on received signal strength information that employs a location ordering strategy and a numerical nonlinear optimization method. The algorithm performance is evaluated through simulation for different network scenarios. A real wireless network scenario is also implemented in order to demonstrate the algorithm effectiveness. The proposed algorithm, while presenting a simplified implementation, can achieve better positioning estimates than the classical MLE approach based on the conjugated gradient.

关键词： Wireless networks positioning algorithms Received signal strength

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Navigation and positioning technology in underground coal mines and tunnels: A review

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JOURNAL OF THE SOUTHERN AFRICAN INSTITUTE OF MINING AND METALLURGY 2021年第6期121卷 295-303页

作者： Cui, Y. Liu, S. Liu, Q. China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Jiangsu Peoples R China China Univ Min & Technol Jiangsu Collaborat Innovat Ctr Intelligent Min Eq Xuzhou 221116 Jiangsu Peoples R China

To reduce the frequency of mining incidents and improve safety and production efficiency, it is important to develop technology for the autonomous positioning and navigation of mining equipment, without the assistance of satellite navigation signals. In this study we review the current technological environment for positioning and navigation underground and present several integrated navigation strategies. Existing underground positioning and navigation technology is described, and the performances of different methods based on this technology analysed and compared. The combination types and positioning effects of underground positioning and navigation strategies are discussed. Recent research directions for filtering methods and positioning estimation algorithms for underground positioning and navigation are reviewed. Finally, we summarize the future direction of underground positioning and navigation technology and related algorithms.

关键词： coal mining underground positioning and navigation integrated navigation strategy inertial navigation positioning algorithms

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Underground mining intelligent response and rescue systems

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Procedia Earth and Planetary Science 2009年第1期1卷 1044-1053页

作者： Zhang, Ke-fei Zhu, Ming Wang, Yun-jia Fu, Er-jiang Cartwright, William School of Mathematical and Geospatial Sciences RMIT University Melbourne Australia School of Environmental Science and Spatial Informatics China University of Mining and Technology Xuzhou 221116 China

Coal mine industry, which produces the most abundant and widely-distributed fossil fuel, is the deadliest in casualties. A recent report shows that the casualty rates of coal production per million tones are 4.36 in China, 2.14 in Ukraine, 2.03 in Russia, 0.088 in USA and 0.08 in Australia respectively. Consequently, safety is a critical issue for the mining industry, especially for the underground mining companies. The modernization and informatization of mining companies have significantly improved the operational environments (and hence safety) for the underground miners. Some advanced technologies, such as the intelligent response and rescue systems, have contributed significantly to the reduction of mining fatalities and accidents. Typical underground positioning and three dimensional (3D) modelling techniques are discussed in this paper first. A RFID/INS integrated positioning system has been tested to evaluate its performance and different positioning algorithms have been implemented. Experiments show that the simple centre of origin (CoO) positioning algorithm can achieve a positioning accuracy of 7.9 m. The integrated fingerprinting algorithm can achieve 1.7 m accuracy by using an Extended Kalman Filter. A new underground structure modelling method and a collision detecting method are developed. A prototype intelligent response and rescue system has been implemented in Da Zhuang coal mine, China. The results indicate that both the underground positioning technique and the 3D modelling and representing technique developed can satisfy the requirements of underground rescue in an emergency situation. © 2009.

关键词： Three dimensional Cellular radio systems Coal Coal industry Coal mines Cobalt compounds Control theory Fossil fuels Mine rescue Mines Mining Underground structures 3D modelling Advanced technology Australia Casualty rate Coal production Critical issues Detecting methods Emergency situation Fingerprinting algorithm Informatization Integrated positioning system Mining companies Mining fatalities Mining industry Modelling techniques Operational environments positioning accuracy positioning algorithms positioning techniques Rescue systems Three dimensional (3D) Ukraine Underground mining

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RobustPathFinder: Handling Uncertainty in Indoor positioning Techniques

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Procedia Computer Science 2018年 130卷 408-415页

作者： José Cecílio Karen Duarte Pedro Martins Pedro Furtado University of Coimbra Coimbra Portugal University of Lisbon Lisbon Portugal Polytechnic Institute of Viseu Viseu Portugal

Indoor navigation technologies rely on accurately determining the position of a moving person or robot to guide her actively through the building. This cannot be done using GPS because it is indoors. We have been dealing with this problem in the context of designing and building a system for helping blind people navigate in public buildings. However, indoor localization based on RSSI is not very accurate, since the quality of the signal is influenced by many factors that include, for instance, wall reflections or people passing by. The fact that the person is moving also introduces several degrees of uncertainty, including a changing number and placement of beacons in-range. The challenge is therefore to develop mechanisms to handle uncertainty. In this paper we propose and evaluate uncertainty-handling mechanisms.

关键词： Indoor positioning Location positioning algorithms Wireless Sensors Beacons RSSI

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A Survey of Smartphone-Based Indoor positioning System Using RF-Based Wireless Technologies

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SENSORS 2020年第24期20卷 7230页

作者： Subedi, Santosh Pyun, Jae-Young Chosun Univ Dept Informat & Commun Engn Kwangju 501759 South Korea

In recent times, social and commercial interests in location-based services (LBS) are significantly increasing due to the rise in smart devices and technologies. The global navigation satellite systems (GNSS) have long been employed for LBS to navigate and determine accurate and reliable location information in outdoor environments. However, the GNSS signals are too weak to penetrate buildings and unable to provide reliable indoor LBS. Hence, GNSS's incompetence in the indoor environment invites extensive research and development of an indoor positioning system (IPS). Various technologies and techniques have been studied for IPS development. This paper provides an overview of the available smartphone-based indoor localization solutions that rely on radio frequency technologies. As fingerprinting localization is mostly accepted for IPS development owing to its good localization accuracy, we discuss fingerprinting localization in detail. In particular, our analysis is more focused on practical IPS that are realized using a smartphone and Wi-Fi/Bluetooth Low Energy (BLE) as a signal source. Furthermore, we elaborate on the challenges of practical IPS, the available solutions and comprehensive performance comparison, and present some future trends in IPS development.

关键词： indoor positioning system fingerprinting localization Bluetooth low energy Wi-Fi performance metrics positioning algorithms

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Research on Indoor positioning Technology Based on UWB

Research on Indoor Positioning Technology Based on UWB

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第32届中国控制与决策会议

作者： Ning Wang Xulin Yuan Lixin Ma Xincheng Tian School of Control Science and Engineering Shandong University

In this paper,the indoor positioning technology based on UWB is *** anchor is embedded with POE technology,realizing the integration of long-term stable power supply and data communication.A variety of positioning algorithms are compared and analyzed,including Trilateration algorithm,Fang algorithm,Chan algorithm in the case of 3 anchors and Taylor algorithm,Chan algorithm in the case of multiple *** various factors,Taylor algorithm in the case of 4 anchors is finally selected as the core positioning *** moving average preprocessing of the original ranging data is carried out to reduce the random *** function of one-key ranging fitting compensation based on least square method is developed,which can reduce the system error and improve the adaptability to different indoor *** result of Trilateration algorithm with the lowest complexity is taken as the initial iterative value of Taylor algorithm,which effectively shorten the time of positioning *** filter is used to process the positioning results,which greatly improves the positioning stability and dynamic tracking *** the laboratory environment,the positioning accuracy of UWB indoor positioning system in this paper can reach ±10 cm.

关键词： Indoor positioning UWB positioning algorithms Kalman Filter Ranging Fitting Compensation

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An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare

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SENSORS 2022年第21期22卷 8119-8119页

作者： Bibbo, Luigi Carotenuto, Riccardo Della Corte, Francesco Univ Mediterranea Reggio Calabria Dept Informat Infrastruct & Sustainable Energy En I-89060 Reggio Di Calabria Italy Univ Napoli Federico II Dept Elect Engn & Informat Technol I-80125 Naples Italy

The number of older people needing healthcare is a growing global phenomenon. The assistance in long-term care comprises a complex of medical, nursing, rehabilitation, and social assistance services. The cost is substantial, but technology can help reduce spending by ensuring efficient health services and improving the quality of life. Advances in artificial intelligence, wireless communication systems, and nanotechnology allow the creation of intelligent home care systems avoiding hospitalization with evident cost containment. They are capable of ensuring functions of recognition of activities, monitoring of vital functions, and tracking. However, it is essential to also have information on location in order to be able to promptly intervene in case of unforeseen events or assist people in carrying out activities in order to avoid incorrect behavior. In addition, the automatic detection of physical activities performed by human subjects is identified as human activity recognition (HAR). This work presents an overview of the positioning system as part of an integrated HAR system. Lastly, this study contains each technology's concepts, features, accuracy, advantages, and limitations. With this work, we want to highlight the relationship between HAR and the indoor positioning system (IPS), which is poorly documented in the literature.

关键词： human activity recognition indoor localization human tracking signal measurement positioning algorithms GPS IPS

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Fundamental Concepts and Evolution of Wi-Fi User Localization: An Overview Based on Different Case Studies

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SENSORS 2020年第18期20卷 5121.-5121.页

作者： Retscher, Guenther TU Wien Dept Geodesy & Geoinformat A-1040 Vienna Austria

Indoor positioning poses a number of challenges, especially in large and complex buildings. Several effects, such as signal attenuation, signal fluctuations, interference, and multipath play a decisive role in signal propagation. The severity of each challenge depends on the method and technology adopted to perform user localization. Wi-Fi is a popular method because of its ubiquity with already available public and private infrastructure in many environments and the ability for mobile clients, such as smartphones, to receive these signals. In this contribution, the fundamental concepts and basics and the evolution of Wi-Fi as the most widely used indoor positioning technology are reviewed and demonstrated using four different conducted case studies. Starting from an analysis of the properties of Wi-Fi signals and their propagation, suitable techniques are identified. The mathematical models of location fingerprinting and lateration are consolidated and assessed as well as new technology directions and developments highlighted. Results of the case studies demonstrate the capability of Wi-Fi for continuous user localization also in dynamic environments and kinematic mode where the user walks with a usual step speed. However, to achieve acceptable localization accuracy, calibration of the devices is required to mitigate the variance problems due to the device heterogeneity.

关键词： received signal strength RSS round trip time RTT measurements location fingerprinting lateration combination and fusion of techniques positioning algorithms indoor smartphone user localization

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Improving Real-Time Position Estimation Using Correlated Noise Models

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SENSORS 2020年第20期20卷 5913.-5913.页

作者： Martin, Andrew Parry, Matthew Soundy, Andy W. R. Panckhurst, Bradley J. Brown, Phillip Molteno, Timothy C. A. Schumayer, Daniel Univ Otago Dept Phys 730 Cumberland St Dunedin 9016 New Zealand Univ Otago Dept Math & Stat 730 Cumberland St Dunedin 9016 New Zealand

We provide algorithms for inferring GPS (Global positioning System) location and for quantifying the uncertainty of this estimate in real time. The algorithms are tested on GPS data from locations in the Southern Hemisphere at four significantly different latitudes. In order to rank the algorithms, we use the so-called log-score rule. The best algorithm uses an Ornstein-Uhlenbeck (OU) noise model and is built on an enhanced Kalman Filter (KF). The noise model is capable of capturing the observed autocorrelated process noise in the altitude, latitude and longitude recordings. This model outperforms a KF that assumes a Gaussian noise model, which under-reports the position uncertainties. We also found that the dilution-of-precision parameters, automatically reported by the GPS receiver at no additional cost, do not help significantly in the uncertainty quantification of the GPS positioning. A non-learning method using the actual position measurements and employing a constant uncertainty does not even converge to the correct position. Inference with the enhanced noise model is suitable for embedded computing and capable of achieving real-time position inference, can quantify uncertainty and be extended to incorporate complementary sensor recordings, e.g., from an accelerometer or from a magnetometer, in order to improve accuracy. The algorithm corresponding to the augmented-state unscented KF method suggests a computational cost of O(dx2dt), where dx is the dimension of the augmented state-vector and dt is an adjustable, design-dependent parameter corresponding to the length of "past values" one wishes to keep for re-evaluation of the model from time to time. The provided algorithm assumes dt=1. Hence, the algorithm is likely to be suitable for sensor fusion applications.

关键词： GPS uncertainty quantification sensor fusion noise models embedded computing system performance evaluation positioning algorithms

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Fusing Bluetooth Beacon Data with Wi-Fi Radiomaps for Improved Indoor Localization

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SENSORS 2017年第4期17卷 812-812页

作者： Kanaris, Loizos Kokkinis, Akis Liotta, Antonio Stavrou, Stavros Eindhoven Univ Technol Dept Elect Engn NL-5600 MB Eindhoven Netherlands Open Univ Cyprus Fac Pure & Appl Sci CY-2252 Nicosia Cyprus

Indoor user localization and tracking are instrumental to a broad range of services and applications in the Internet of Things (IoT) and particularly in Body Sensor Networks (BSN) and Ambient Assisted Living (AAL) scenarios. Due to the widespread availability of IEEE 802.11, many localization platforms have been proposed, based on the Wi-Fi Received Signal Strength (RSS) indicator, using algorithms such as K-Nearest Neighbour (KNN), Maximum A Posteriori (MAP) and Minimum Mean Square Error (MMSE). In this paper, we introduce a hybrid method that combines the simplicity (and low cost) of Bluetooth Low Energy (BLE) and the popular 802.11 infrastructure, to improve the accuracy of indoor localization platforms. Building on KNN, we propose a new positioning algorithm (dubbed i-KNN) which is able to filter the initial fingerprint dataset (i. e., the radiomap), after considering the proximity of RSS fingerprints with respect to the BLE devices. In this way, i-KNN provides an optimised small subset of possible user locations, based on which it finally estimates the user position. The proposed methodology achieves fast positioning estimation due to the utilization of a fragment of the initial fingerprint dataset, while at the same time improves positioning accuracy by minimizing any calculation errors.

关键词： indoor positioning indoor localization fingerprint bluetooth low energy (BLE) Internet of Things (IoT) Body Sensor Networks (BSN) positioning algorithms

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