Harvesting Indoor Positioning Accuracy by Exploring Multiple Features From Received Signal Strength Vector
                    
                        
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                    چکیده
منابع مشابه
Π8: Indoor Positioning System using WLAN Received Signal Strength Measurements
In this deliverable we provide the details of building an indoor positioning system using WLAN Received Signal Strength (RSS) fingerprints. The positioning system has been deployed at the premises of KIOS Research Center and follows a terminal-based-network-assisted architecture. In our case, users that carry a terminal (Tablet PC) are able to self-locate and positioning is performed entirely o...
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Considering that indoor positioning applications based on wireless local area network location fingerprinting would be mainly used on the mobile devices. This paper investigates the differences of received signal strength indication (RSSI) between different smart phones and the distributions of RSSI are also analyzed. The statistical analysis of experimental results shows the differences of RSS...
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The main approach for a Wi-Fi indoor positioning system is based on the received signal strength (RSS) measurements, and the fingerprinting method is utilized to determine the user position by matching the RSS values with the pre-surveyed RSS database. To build a RSS fingerprint database is essential for an RSS based indoor positioning system, and building such a RSS fingerprint database requir...
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Localization for mobile wireless sensor networks has been intensively studied in recent years due to its many applications in mobile networking as well as various public safety problems. However, the complexity of indoor radio propagation, especially when considering mobile users, makes indoor positioning a challenging task. This is mainly due to the severe multipath phenomenon where multiple c...
متن کاملExperimental Performance Comparison of Indoor Positioning Algorithms based on Received Signal Strength
The work presented here compares the performance of indoor positioning systems suitable for low power wireless sensor networks. Map matching, approximate positioning (weighted centroid) and exact positioning algorithms (least squares) were tested and compared in a small predefined indoor environment. We found that, for our test scenario, weighted centroid algorithms provided the best results. L...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2911601