Results 171 to 180 of about 12,611 (225)
Drone Controller Localization Based on RSSI Ratio
Sensors, 2023 We proposed two methods for the localization of drone controllers based on received signal strength indicator (RSSI) ratios: the RSSI ratio fingerprint method and the model-based RSSI ratio algorithm.
Sun Sumei, Yuhong Wang, Yugang Ma
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Wireless RSSI fingerprinting localization
Signal Processing, 2017Localization has attracted a lot of research effort in the last decade due to the explosion of location based service (LBS). In particular, wireless fingerprinting localization has received much attention due to its simplicity and compatibility with existing hardware.
Simon Yiu +3 more
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mmWaves RSSI indoor network localization
2014 IEEE International Conference on Communications Workshops (ICC), 2014Indoor positioning gained great interest in recent years. Several performance evaluations are available for consolidated systems, especially for ultra-wideband radios. Given the current success of mmWaves networks, in this paper, we investigate the performance of RSSI localization systems operating at mmWaves.
Vari M, CASSIOLI, DAJANA
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Localization Sensitivity Under RSSI Quantization
ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 2019Received Signal Strength Indication (RSSI) is a notoriously noisy metric, yet attractive for localization purposes. We study the effect of reducing the RSSI value to a single bit, essentially turning the RSSI measurement into a proximity indicator.
Alan Yong +2 more
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RSSI localization method for mine underground based on RSSI hybrid filtering algorithm
2017 IEEE 9th International Conference on Communication Software and Networks (ICCSN), 2017Aiming at the coal mine personnel positioning method based on wireless sensor network technology, contrasting with advantage of now-existing feasible methods, consulting with traditional trilateral positioning, this paper proposed weighted trilateral localization method based on RSSI ranging.
Liu Yi, Liang Tao, Sun Jun
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RSSI localisation with sensors placed on the user
2010 International Conference on Indoor Positioning and Indoor Navigation, 2010We examine the indoor single-room localisation problem while using multiple fixed transmitters (anchors) and multiple mobile receivers placed on the user (mobiles). Anchors transmit a periodic beacon that the mobiles receive and of which they measure the received power level value (RSSI).
Barsocchi P. +3 more
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3D Outdoor Positioning Based on RSSI
2018 10th International Conference on Wireless Communications and Signal Processing (WCSP), 2018As a key feature of wireless sensor networks, location-based services find wide applications in social networks, e.g., emergency, navigation and marketing. However, most positioning algorithms aim at two-dimensional indoor applications and few have focused on three-dimensional (3D) outdoor applications.
Wanjing Kuang +4 more
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Predicting Car Collisions Using RSSI
2015 IEEE Global Communications Conference (GLOBECOM), 2014The periodic broadcast of a safety message (SM) containing vehicle position and motion data is the salient mechanism for providing drivers pre-crash alerts in Vehicle-to-Vehicle (V2V) networks. However, if SMs are compromised or contain erroneous information, drivers may be unaware of impending danger.
Billy Kihei +2 more
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Metric Learning for Fingerprint RSSI-Localization
2020 IEEE/ION Position, Location and Navigation Symposium (PLANS), 2020In this paper, we describe a framework dedicated to the geolocation of devices that can only be positioned in a set of specific locations called points of interest (noted PoIs). After a short introduction explaining the importance of this topic, a machine learning approach of this problem will be formalized and some of the off-the-shelf predictors that
Kevin Elgui +4 more
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RSSI Localization with Gaussian Processes and Tracking
2015 IEEE Globecom Workshops (GC Wkshps), 2015Location Fingerprinting (LF) is a promising localization technique that enables many commercial and emergency location-based services (LBS). While significant efforts have been invested in enhancing LF using advanced machine learning methods, the configuration effort required to deploy a LF system remains a significant issue. In this paper, a practical
Marzieh Dashti +4 more
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