Exploiting RF-Scatter: Human Localization with Bistatic Passive UHF RFID-Systems

Lieckfeldt, Dominik; You, Jiaxi; Timmermann, Dirk

doi:10.1109/wimob.2009.39

Cited by 17 publications

(15 citation statements)

References 6 publications

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“…1. The results provide a maximum RMSE of 0.75 m [1].  Geometric localization based on Linear Least Squares and Intersection Points applied on the measured signal strength differences.…”

Section: A Passive Rfid Positioningmentioning

confidence: 96%

“…Dealing with the problem of energy efficiency and deployment complexity we invented an approach utilizing ground mounted passive Radio Frequency Identification Tags (RFID) for device-free radio-based recognition [1], [3], [4]. This work has shown that it is possible to calculate 2D user positions with remarkable accuracy [4] and low computational complexity.…”

Section: A Passive Rfid Positioningmentioning

confidence: 99%

“…Another big advantage are the costs: RFID transponders can be purchased very cheap, as low as 0.20 € per item. Based on that, multiple localization algorithms were proposed in the past providing positioning results with an error as low as 0.3 m in 2D scenarios [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

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Approaches for device-free multi-user localization with passive RFID

Wagner

Timmermann

2013

International Conference on Indoor Positioning and Indoor Navigation

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User localization information is an important data source for ubiquitous assistance in smart environments and other location aware systems. Mostly there is a need for non-invasive, wireless, privacy preserving technologies. Device-free localization approaches (DFL) provide these advantages with no need for user-attached hardware. A common goal within the research of DFL technologies is the distinction and tracking of multiple users in an indoor scenario. In our recent work we show that DFL approaches utilizing completely passive RFID transponders can localize one person very precisely. In this work we show basic approaches and conduct first experiments in an indoor room DFL scenario for proof of concept and validation. We show that it is possible to distinguish between two users with reasonable precision and computation demand.

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“…1. The results provide a maximum RMSE of 0.75 m [1].  Geometric localization based on Linear Least Squares and Intersection Points applied on the measured signal strength differences.…”

Section: A Passive Rfid Positioningmentioning

confidence: 96%

Section: A Passive Rfid Positioningmentioning

confidence: 99%

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Approaches for device-free multi-user localization with passive RFID

Wagner

Timmermann

2013

International Conference on Indoor Positioning and Indoor Navigation

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“…A variety of RFID-based IPSs by adopting passive RFID tags have been proposed in recent two decades [17,18]. Although they are lighter and less expensive than active tags, the range of the passive RFID tags is limited to approximately 1 to 2 m which largely restricts the coverage area of their system [19].…”

Section: Rfid-based Ipsmentioning

confidence: 99%

Platform and Algorithm Development for a RFID-Based Indoor Positioning System

et al. 2014

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In recent years, developing Indoor Positioning System (IPS) has become an attractive research topic due to the increasing demands on Location-Based Service (LBS) in indoor environment. Several advantages of Radio Frequency Identification (RFID) Technology, such as anti-interference, small, light and portable size of RFID tags, and its unique identification of different objects, make it superior to other wireless communication technologies for indoor positioning. However, certain drawbacks of existing RFID-based IPSs, such as high cost of RFID readers and active tags, as well as heavy dependence on the density of reference tags to provide the LBS, largely limit the application of RFID-based IPS. In order to overcome these drawbacks, we develop a cost-efficient RFID-based IPS by using cheaper active RFID tags and sensors. Furthermore, we also proposed three localization algorithms: Weighted Path Loss (WPL), Extreme Learning Machine (ELM) and integrated WPL-ELM. WPL is a centralized model-based approach which does not require any reference tags and provides accurate location estimation of the target effectively. ELM is a machine learning fingerprinting-based localization algorithm which can provide higher localization accuracy than other existing fingerprinting-based approaches. The integrated WPL-ELM approach combines the fast estimation of WPL and the high localization accuracy of ELM. Based on the experimental results, this integrated approach provides a higher localization efficiency and accuracy than existing approaches, e.g., the LANDMARC approach and the support vector machine for regression (SVR) approach.

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“…In addition, Yang et al [7] introduced a method using a compressed infrared bearing sensor for human localization as infrared detectors are sensitive to the change of infrared radiation induced by human motions. In [8], an approach for human localization using a passive UHF RFID was presented. The idea is to characterize the change of RSSI caused by the presence of a person inside an RFID augmented deployment area.…”

Section: Introductionmentioning

confidence: 99%