In recent years, positioning systems for indoor areas using the existing wireless local area network infrastructure have been suggested. Such systems make use of location fingerprinting rather than time or direction of arrival techniques for determining the location of mobile stations. While experimental results related to such positioning systems have been presented, there is a lack of analytical models that can be used as a framework for designing and deploying the positioning systems. In this paper, we present an analytical model for analyzing such positioning systems. We develop the framework for analyzing a simple positioning system that employs the Euclidean distance between a sample signal vector and the location fingerprints of an area stored in a database. We analyze the effect of the number of access points that are visible and radio propagation parameters on the performance of the positioning system and provide some preliminary guidelines on its design.

Context-aware computing is an emerging computing paradigm that can provide new or improved services by exploiting user context information. In this paper, we present a wireless-localarea-network-based (WLAN-based) indoor positioning technology. The wireless device deploys a positiondetermination model to gather location information from collected WLAN signals. A model-based signal distribution training scheme is proposed to trade off the accuracy of signal distribution and training workload. A tracking-assistant positioning algorithm is presented to employ knowledge of the area topology to assist the procedure of position determination. We have set up a positioning system at the IBM China Research Laboratory. Our experimental results indicate an accuracy of 2m with a 90% probability for static devices and, for moving (walking) devices, an accuracy of 5m with a 90% probability. Moreover, the complexity of the training procedure is greatly reduced compared with other positioning algorithms.

As well as delivering high speed internet, Wireless LAN (WLAN) can be used as an effective indoor positioning system. It is competitive in terms of both accuracy and cost compared to similar systems. To date, several signal strength based techniques have been proposed. Researchers at the University of New South Wales (UNSW) have developed several innovative implementations of WLAN positioning systems. This paper describes the techniques used and details the experimental results of the research.

The knowledge of the location of a mobile terminal can be used to reduce the cognitive burden on the users in context-aware systems and it is a crucial information for routing in ad-hoc networks and for optimizing the topology in order to minimize the energy consumption of the nodes. The strengths of the RF signals arriving from more access points are related to the position (location fingerprinting), but the complexity of the inverse problem to derive the position from the signals and the lack of complete information, motivate to consider flexible models based on a network of functions (neural networks), developed through a supervised learning strategy. The advantage

Detecting the user location is crucial in a wireless environment, not only for the choice of first-hop communication partners, but also for many auxiliary purposes: Quality of Service (availability of information in the right place for reduced congestion /delay, establishment of the optimal path), energy consumption, automated insertion of location-dependent info into a web query issued by a user (for example a tourist asking informations about a monument or a restaurant, a fireman approaching a disaster area).

journal homepage: www.elsevier.com/locate/eswa

Abstract — This paper presents the research activities carried out within the scope of the Liaison project. Most of the work has been performed on WiFi location. WiFi is nowadays widely deployed in buildings such as hotels, hospitals, airports, train stations, public buildings, etc. Using this infrastructure to locate terminals connected to the wireless LAN is expected to have a low cost. Methods presented in this paper include fingerprinting and tracking through particle filter constrained on a Voronoi diagram and TOA based on data frames and acknowledgments at the link level. Other technologies have also been researched: A-GNSS to handle the transition between outdoors and indoors, UWB in ad-hoc mode to cope with possible lacks of infrastructure and inertial MEMS to increase the availability and robustness of the overall system. A. Location Based Services I.

To date many positioning systems are available to determine or track a user’s location; three main categories include Global Positioning System (GPS), wide area location system and indoor positioning system. GPS has its limitation (poor signals) in indoor or urban uses, while wide-area location systems are cellular networks dependent. For indoor positioning system many approaches like infrared sensing, radio frequency, ultrasonic etc. are proposed; each of these methods has their own advantages and disadvantages. Considering cost-effectiveness, speed and accuracy a recent interest is growing on using wireless technology. A Wireless Local-Area Network (WLAN) based positioning system has some distinct advantages like low-cost and wider area coverage. This researrch propose a system to determine the location of a mobile terminal or a handheld PDA in high speed, low-cost wireless networks by using the wireless communications infrastructure. The experimental set up used an indoor wireless facility of an auditorium, where signals from three Access Points (APs) were recorded to train a position determination model to calculate and map a position. Grid model was applied and compare the resulted position of a client. A handheld PDA equipped with application software was the client device. The accuracy assessment has been performed to identify the distance errors and the average distance error was found lowest for the grid model. The results of the experiments reveal that the accuracy of 0.05 m can be achieved.

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In Wireless Sensor Network (WSN) applications it is critical to accurately determine the location of the distributed sensor nodes in order to report the data that is geographically meaningful. Since localization and tracking algorithms have been attracting research and development attention recently, a wide range of existing approaches regarding this topic have emerged. Tracking and localization algorithms have been proposed for different WSN applications including civilian, industrial and safety applications. A few research studies focused on tracking Threats through military applications, such as detecting and tracking Threats through border security area. Therefore this paper studies and investigates the existing WSN based tracking and localization algorithms and summarizes the potential requirements for localizing and tracking Threats through military applications. The existing systems are categorized and discussed. A critical analysis is found in this paper, in order to guide the developer to design and implement a WSN-based tracking system for military applications.