An Indoor Localization Mechanism Using Active RFID Tag

Jin, Guang-yao; Lu, Xiao-yi; Park, Myong-Soon

doi:10.1109/sutc.2006.1636157

Cited by 45 publications

(21 citation statements)

References 5 publications

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“…R fingerprint vector at point P is also recorded and sent to PC during on-line phase, [11,12].The Euclidean distance, E, between F and R vectors at any grid point is given by:…”

Section: Fingerprint Localizationmentioning

confidence: 99%

Virtual 2D Positioning System by Using Wireless Sensors in Indoor Environment

Koyuncu¹,

Yang²

2013

IJWMN

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“…R fingerprint vector at point P is also recorded and sent to PC during on-line phase, [11,12].The Euclidean distance, E, between F and R vectors at any grid point is given by:…”

Section: Fingerprint Localizationmentioning

confidence: 99%

Virtual 2D Positioning System by Using Wireless Sensors in Indoor Environment

Koyuncu¹,

Yang²

2013

IJWMN

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“…In fact, a spectacular growth of studies about indoor location has been witnessed since RADAR [3] was proposed in 2000. The ubiquity of Wi-Fi Internet connectivity and smartphones make Wi-Fi-based positioning very popular [3,41,17,22,60,47,49,11,39,42], despite the diversity of the technologies available for indoor positioning: Radio-Frequency Identification (RFID) [33,51,9], Bluetooth [20,44], ZigBee [50], Ultrasound [30,26,55], Magnetic field variations [14,27], LED light [38,34], Ultra Wide Band [25,23], and Hybrid solutions [32], among others. The IPSs based on Wi-Fi fingerprinting techniques are preferred to those based on the propagation model, angle of arrival, time of arrival and time difference of arrival because they do not require any very specialized hardware, line-of-sight to the emitter, or knowledge about the precise location of radio emitters to operate [71,70].…”

Section: Introductionmentioning

confidence: 99%

A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competition

Torres-Sospedra

Moreira

Knauth

et al. 2017

AIS

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Abstract. This paper presents results from comparing different Wi-Fi fingerprinting algorithms on the same private dataset. The algorithms where realized by independent teams in the frame of the off-site track of the EvAAL-ETRI Indoor Localization Competition which was part of the Sixth International Conference on Indoor Positioning and Indoor Navigation (IPIN 2015). Competitors designed and validated their algorithms against the publicly available UJIIndoorLoc database which contains a huge reference-and validation data set. All competing systems were evaluated using the mean error in positioning, with penalties, using a private test dataset. The authors believe that this is the first work in which Wi-Fi fingerprinting algorithm results delivered by several independent and competing teams are fairly compared under the same evaluation conditions. The analysis also comprises a combined approach: Results indicate that the competing systems where complementary, since an ensemble that combines three competing methods reported the overall best results.

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“…[6] has contributed an idea to improve the positioning accuracy by means of eliminating diversity of tags. [7] has proposed a method to overcome the defect of LANDMARC algorithm caused by high density of reference tags and high complexity of computing. [8] introduce event-based possibility model to describe experiment environment interference and use PSO-based optimal algorithm to optimize positioning result.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fitting Reference Frame for 2-D Indoor Localization Based on RFID

Yang¹,

Chen²

2014

IJET

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Abstract-Indoor localization information is important to many different industries. Ever-rising demand from both custom and supplier pose great challenge for indoor localization technology. The emergence of rapid development of Radio Frequency Identification (RFID) technology enriches indoor positioning methodology. Traditional indoor localization algorithm mainly based on the signal propagation property. Among all of positioning algorithm, LANDMARC is most promising one but still has some limitation such as multipath effect, noise form environment and quantity constrain of tags. This paper identifies previous RFID-based indoor localization algorithm and proposes a new algorithm aiming at delivering above limitation to estimate objective position indoor environment. It use RSS propagation curve to obtain RSS value of virtual reference tag, and then estimate target tags position. To evaluate its performance, a comparison between LANDMARC and proposed algorithm was conducted. Experiment result show proposed algorithm is more accurate than LANDMARC.

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An Indoor Localization Mechanism Using Active RFID Tag

Cited by 45 publications

References 5 publications

Virtual 2D Positioning System by Using Wireless Sensors in Indoor Environment

Virtual 2D Positioning System by Using Wireless Sensors in Indoor Environment

A realistic evaluation of indoor positioning systems based on Wi-Fi fingerprinting: The 2015 EvAAL–ETRI competition

Adaptive Fitting Reference Frame for 2-D Indoor Localization Based on RFID

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