863 research outputs found

    Enhancement of weighted centroid algorithm for indoor mobile non-cooperative localization system

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    Nowadays, indoor wireless localization is being challenged research by providing high accuracy of location information. However lower processing time, resistant to environmental condition, simple network topology are also become main concern. Noncooperative localization based on RSSI allow the anchor nodes as the reference nodes communicate directly to the target node by exchanging the location data. High sensitivity of RSSI to the indoor environment, make difficulties in modelling propagation characteristic called as PLE. Incompatibility the PLE value can influence to the estimated position result. Weighted centroid localization (WCL) is feasible solution for RSSI-based that can obtain the target node location just by RSSI and anchor nodes coordinate without PLE value and estimated distance. While, the centroid determination of WCL give better estimation only to the centralized position of target node between all anchor nodes position. Therefore, we propose enhancement of WCL (eWCL) by replacing the weight based on RSSI with different estimated distance from WCL calculation. The simulation result show that using eWCL can reduce the error estimation around 60.42% compared to the WCL algorithm with 1.85 meters MSE value. Then, compared to the cooperative localization based on trilateration algorithm achieve 12.15% error estimation larger than eWCL at non-cooperative scheme

    Localization for Emergency Sensor Networks

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    Radio Frequency-Based Indoor Localization in Ad-Hoc Networks

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    The increasing importance of location‐aware computing and context‐dependent information has led to a growing interest in low‐cost indoor positioning with submeter accuracy. Localization algorithms can be classified into range‐based and range‐free techniques. Additionally, localization algorithms are heavily influenced by the technology and network architecture utilized. Availability, cost, reliability and accuracy of localization are the most important parameters when selecting a localization method. In this chapter, we introduce basic localization techniques, discuss how they are implemented with radio frequency devices and then characterize the localization techniques based on the network architecture, utilized technologies and application of localization. We then investigate and address localization in indoor environments where the absence of global positioning system (GPS) and the presence of unique radio propagation properties make this problem one of the most challenging topics of localization in wireless networks. In particular, we study and review the previous work for indoor localization based on radio frequency (RF) signaling (like Bluetooth‐based localization) to illustrate localization challenges and how some of them can be overcome

    A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives

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    Efficient localization plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would contribute to improved control, safety, power economy, etc. The ubiquitous 5G NR (New Radio) cellular network will provide new opportunities for enhancing localization of UAVs and UGVs. In this paper, we review the radio frequency (RF) based approaches for localization. We review the RF features that can be utilized for localization and investigate the current methods suitable for Unmanned vehicles under two general categories: range-based and fingerprinting. The existing state-of-the-art literature on RF-based localization for both UAVs and UGVs is examined, and the envisioned 5G NR for localization enhancement, and the future research direction are explored

    A Survey on Localization Methods in Intelligent Transportation System

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    Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such networks, location is being used to identify the location at which sensor readings originate. In this paper, a survey of the localization methods in the wireless sensor networks is presented.The contribution of this survey is to give a classi?cation of existing ?ngerprintbasedlocalizationapproacheswhichintelligentlysenseandmatch different clues from the environment to identify location

    Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization

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    The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network). The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling

    Body attenuation and path loss exponent estimation for RSS-based positioning in WSN

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    The influence of the human body in antenna systems has significant impact in the received signal strength (RSS) of wireless transmissions. Accounting for body effect is generally considered as being able to improve position estimation based on RSS measurements. In this work we perform several experiments with a wireless sensor network, using a sensor node equipped with an inertial measurement unit (IMU), in order to obtain the relative orientation between the sensor node and multiple anchor nodes. A model of the RSS attenuation induced by the body was created using experimental measurements in a controlled environment and applied to a real-time positioning system. A path loss exponent (PLE) estimation method using RSS information from neighbor anchors was also implemented and evaluated. Weighted centroid localization (WCL) algorithm was the positioning method used in this work. When the sensor node was placed on the user’s body, accounting for body effect produced negligible improvements (6%) in the best-case scenario and consistently degraded accuracy under real conditions, whether the node was placed on the user’s body (in the order of 3%), 10 cm away (from 14% to 35%) or 20 cm away from the body (from 42% to 105%) for results in the 70th percentile. The PLE estimation method showed improvements (in the order of 11%) when the sensor node is further away from the body. Results demonstrate that the distance between sensor node and the body has an extremely important influence on the accuracy of the position estimate.This work has been supported by FCT (Fundação para a CiĂȘncia e Tecnologia) in the scope of the project UID/EEA/04436/2013. Helder D. Silva is supported by FCT under the grant SFRH/BD/78018/2011info:eu-repo/semantics/publishedVersio
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