Wireless Local Area Network (WLAN) has been an emerging technology in residential and enterprise market by providin- hi-h data rates at low cost. Future trends in WLAN industry are targeted towards new applications wi...
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ISBN:
(纸本)0780389662
Wireless Local Area Network (WLAN) has been an emerging technology in residential and enterprise market by providin- hi-h data rates at low cost. Future trends in WLAN industry are targeted towards new applications with higher data rates, L-h wider coverage, and increased QoS requirements. User tracking system based on WLAN infrastructure is a new service that helps network operators in monitoring different aspects of their networks in addition to providing location aware services to their customers. In this paper, we provide an overview of the traditional location sensing algorithms and compare their performance with the new Distance Variance (DV) algorithm. These algorithms the existing IEEE 802.11 infrastructure to locate a terminal. The newly introduced DV algorithm uses indoor radio propagation models to reduce the complexity of calibration process, used in conventional algorithms. The performances of die existing and new algorithm are compared using Monte Carlo simulations based on IEEE 802.11 channel models.
Indoor positioning Systems (IPSs) for emergency responders is a challenging field attracting researchers worldwide. When compared with traditional indoor positioning solutions, the IPSs for emergency responders stand ...
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Indoor positioning Systems (IPSs) for emergency responders is a challenging field attracting researchers worldwide. When compared with traditional indoor positioning solutions, the IPSs for emergency responders stand out as they have to operate in harsh and unstructured environments. From the various technologies available for the localization process, ultra-wide band (UWB) is a promising technology for such systems due to its robust signaling in harsh environments, through-wall propagation and high-resolution ranging. However, during emergency responders' missions, the availability of UWB signals is generally low (the nodes have to be deployed as the emergency responders enter a building) and can be affected by the non-line-of-sight (NLOS) conditions. In this paper, the performance of four typical distance-based positioning algorithms (Analytical, Least Squares, Taylor Series, and Extended Kalman Filter methods) with only three ranging measurements is assessed based on a COTS UWB transceiver. These algorithms are compared based on accuracy, precision and root mean square error (RMSE). The algorithms were evaluated under two environments with different propagation conditions (an atrium and a lab), for static and mobile devices, and under the human body's influence. A NLOS identification and error mitigation algorithm was also used to improve the ranging measurements. The results show that the Extended Kalman Filter outperforms the other algorithms in almost every scenario, but it is affected by the low measurement rate of the UWB system.
The user location information represents a core dimension as understanding user context is a prerequisite for providing human-centered services that generally improve quality of life. In comparison with outdoor enviro...
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ISBN:
(纸本)9781479946778
The user location information represents a core dimension as understanding user context is a prerequisite for providing human-centered services that generally improve quality of life. In comparison with outdoor environments, sensing location information in indoor environments requires a higher precision and is a more challenging task due in part to the expected various objects (such as walls and people) that reflect and disperse signals. In this paper, we survey the related work in the field of indoor positioning by providing a comparative analysis of the state-of-the-art technologies, techniques, and algorithms. Unlike previous studies and surveys, our survey present new taxonomies, review some major recent advances, and argue on the area open problems and future potential. We believe this paper would spur further exploration by the research community of this challenging problem space.
Acoustic local positioning systems (ALPSs) are an interesting alternative for indoor positioning due to certain advantages over other approaches, including their relatively high accuracy, low cost, and room-level sign...
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Acoustic local positioning systems (ALPSs) are an interesting alternative for indoor positioning due to certain advantages over other approaches, including their relatively high accuracy, low cost, and room-level signal propagation. Centimeter-level or fine-grained indoor positioning can be an asset for robot navigation, guiding a person to, for instance, a particular piece in a museum or to a specific product in a shop, targeted advertising, or augmented reality. In airborne system applications, acoustic positioning can be based on using opportunistic signals or sounds produced by the person or object to be located (e.g., noise from appliances or the speech from a speaker) or from encoded emission beacons (or anchors) specifically designed for this purpose. This work presents a review of the different challenges that designers of systems based on encoded emission beacons must address in order to achieve suitable performance. At low-level processing, the waveform design (coding and modulation) and the processing of the received signal are key factors to address such drawbacks as multipath propagation, multiple-access interference, near-far effect, or Doppler shifting. With regards to high-level system design, the issues to be addressed are related to the distribution of beacons, ease of deployment, and calibration and positioning algorithms, including the possible fusion of information obtained from maps and onboard sensors. Apart from theoretical discussions, this work also includes the description of an ALPS that was implemented, installed in a large area and tested for mobile robot navigation. In addition to practical interest for real applications, airborne ALPSs can also be used as an excellent platform to test complex algorithms (taking advantage of the low sampling frequency required), which can be subsequently adapted for other positioning systems, such as underwater acoustic systems or ultrawideband radiofrequency (UWB RF) systems.
Unmanned Aerial Vehicles (UAVs) are suited as cost-effective and adaptable platforms for carrying Wi-Fi Access Points (APs) and cellular Base Stations (BSs). Implementing aerial networks in disaster management scenari...
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Unmanned Aerial Vehicles (UAVs) are suited as cost-effective and adaptable platforms for carrying Wi-Fi Access Points (APs) and cellular Base Stations (BSs). Implementing aerial networks in disaster management scenarios and crowded areas can effectively enhance Quality of Service (QoS). Maintaining Line-of-Sight (LoS) in such environments, especially at higher frequencies, is crucial for ensuring reliable communication networks with high capacity, particularly in environments with obstacles. The main contribution of this paper is a traffic- and obstacle-aware UAV positioning algorithm named Reinforcement Learning-based Traffic and Obstacle-aware positioning Algorithm (RLTOPA), for such environments. RLTOPA determines the optimal position of the UAV by considering the positions of ground users, the coordinates of obstacles, and the traffic demands of users. This positioning aims to maximize QoS in terms of throughput by ensuring optimal LoS between ground users and the UAV. The network performance of the proposed solution, characterized in terms of mean delay and throughput, was evaluated using the ns-3 simulator. The results show up to 95% improvement in aggregate throughput and 71% in delay without compromising fairness.
This paper considers positioning algorithms for rotary actuators based on shape memory Cu-Al-Ni crystals. The actuator function scheme is provided. An algorithm for positioning of the actuator based on an actual rotar...
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This paper considers positioning algorithms for rotary actuators based on shape memory Cu-Al-Ni crystals. The actuator function scheme is provided. An algorithm for positioning of the actuator based on an actual rotary angle has been developed. Experimental results on the control algorithm and the actuator are presented. The functional characteristics of the actuator (rotation speed and positioning accuracy) are considered.
We address the problem of range-based marine vehicle positioning in the presence of unknown but constant ocean currents. The goal is to estimate the position of one or more vehicles from a sequence of range measuremen...
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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 deal...
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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. (C) 2018 The Authors. Published by Elsevier B.V.
While satellite-based positioning systems are mainly used in outdoor environments, various other positioning techniques exist for different domains and use cases, including indoor or underground settings. The represen...
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ISBN:
(纸本)9783031194320;9783031194337
While satellite-based positioning systems are mainly used in outdoor environments, various other positioning techniques exist for different domains and use cases, including indoor or underground settings. The representation of spatial data via semantic linked data is well addressed by existing spatial ontologies. However, there is a primary focus on location data with its specific geographical context, but a lack of solutions for describing the different types of data generated by a positioning system and the used sampling techniques to obtain the data. In this paper we introduce a new generic positioning System Ontology (POSO) that is built on top of the Semantic Sensor Network (SSN) and Sensor, Observation, Sample, and Actuator (SOSA) ontologies. With POSO, we provide missing concepts needed for describing a positioning system and its output with known positioning algorithms and techniques in mind. Thereby, we enable the improvement of hybrid positioning systems making use of multiple platforms and sensors that are described via the presented POSO ontology.
In this paper, the indoor positioning technology based on UWB is studied. The anchor is embedded with POE technology, realizing the integration of long-term stable power supply and data communication. A variety of pos...
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ISBN:
(纸本)9781728158556
In this paper, the indoor positioning technology based on UWB is studied. The 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 anchors. Considering various factors, Taylor algorithm in the case of 4 anchors is finally selected as the core positioning algorithm. The moving average preprocessing of the original ranging data is carried out to reduce the random error. The 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 environment. The 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 operation. Kalman filter is used to process the positioning results, which greatly improves the positioning stability and dynamic tracking performance. In the laboratory environment, the positioning accuracy of UWB indoor positioning system in this paper can reach +/- 10cm.
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