Experimental Evaluation of Location Methods Based on Signal-Strength Measurements

Laitinen, Heikki; Juurakko, Suvi; Lahti, Tuuli; Korhonen, R.; Lähteenmäki, Jaakko

doi:10.1109/tvt.2006.883785

Cited by 43 publications

(39 citation statements)

References 16 publications

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“…As for detecting locations with RF, there are a lot of work for indoor location system of an RF device [4]- [10]. There is also a work to use bayesian filtering for location detection [11].…”

Section: Related Workmentioning

confidence: 99%

Location Recognition in RFID Bookshelves

Inoue

Nohara

Masaki

et al. 2011

IEICE Trans. Inf. & Syst.

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SUMMARYWe consider RFID bookshelves, which detect the location of books using RFID. An RFID bookshelf has the antennas of RFID readers in the boards, and detects the location of an RFID tag attached to a book. However, the accuracy is not good with the experience of the existing system, and sometimes reads the tag of the next or even further area. In this paper, we propose a method to improve the location detection using naive Bayes classifer, and show the experimental result. We obtained 78.6% of F-measure for total 12658 instances, and show the advantage against the straightforward approach of calculating the center of gravity of the read readers. More importantly, we show the performance is less dependent of a change of layouts and a difference of books by leave-1-layout/book-out cross validation. This is favorable for the feasibility in library operation.

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Section: Related Workmentioning

confidence: 99%

Location Recognition in RFID Bookshelves

Inoue

Nohara

Masaki

et al. 2011

IEICE Trans. Inf. & Syst.

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“…For radio-frequency-based systems, several signal metrics, such as time of flight measurements (TOA, TDOA) and direction of arrival measurements (AoA), were detailed in [2], [3]. Systems based on received signal strength indicators (RSSI) have also been studied extensively, as they have a comparatively low cost and can leverage pre-existing infrastructure, such as Wi-Fi and Bluetooth networks [4].…”

Section: Introductionmentioning

confidence: 99%

“…In [4], [5], a least square (LS) estimator was proposed for RSSI-based location estimation. This linear estimator attempts to minimize the error term between measurements and propagation model.…”

Section: Introductionmentioning

confidence: 99%

RSSI-based indoor tracking using the extended Kalman filter and circularly polarized antennas

Kilani

Raymond

Gagnon

et al. 2014

2014 11th Workshop on Positioning, Navigation and Communication (WPNC)

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Abstract-A tracking scenario comprising a mobile emitter node moving through an indoor environment covered by multiple anchor receivers is investigated in this work. A localization method based on received signal strength indicators (RSSI) and making use of the extended Kalman filter (EKF) and circularly polarized (CP) antennas is proposed. The EKF implements the position-velocity (PV) model, which assumes that the target is moving at a near-constant velocity during any given short time interval ∆t. The measurement vector is composed of velocities in addition to RSSI values, which allow to deal with the error term between measurements and the propagation model directly. CP antennas are used on both the anchor nodes and the mobile node. These antennas are known to reduce the effects of multipath, especially those caused by single reflections. As a result, the RSSI values received in line of sight are more accurate and stable than those received from linearly polarized antennas. We tested our approach by tracking the movement of a robot following a predefined trajectory. The maximum location estimation error (LEE) is found to be 0.52 m. In addition, velocity changes are easily tracked during the target movement, which demonstrates the effectiveness of the proposed approach.

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“…However, only the fixed transmit power case is considered for the primary user. Therefore, in this paper, we consider a more realistic scenario where the transmit power of the primary user fluctuates along with time [8], [9]. In this scenario, we derive a closedform expression for the ergodic capacity of the secondary user considering the effect of the transmit power fluctuation of the primary user.…”

Section: Introductionmentioning

confidence: 99%

Effect of primary power fluctuation on ergodic capacity of a secondary user in a spectrum sharing environment

Noh

Lim

Park

et al. 2014

2014 International Conference on Computing, Networking and Communications (ICNC)

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This paper investigates the effect of the transmit power fluctuation of the primary user on the ergodic capacity of the secondary user in a spectrum sharing environment. Considering an average received-power constraint at the primary user receiver, we derive the closed-form expression for the ergodic capacity of the secondary user and the average received-power assuming Rayleigh fading channels. Numerical results show that the transmit power fluctuation can enhance the ergodic capacity of the secondary user if the secondary user properly control its transmit power so as to fully exploit the transmit power fluctuation.

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Experimental Evaluation of Location Methods Based on Signal-Strength Measurements

Cited by 43 publications

References 16 publications

Location Recognition in RFID Bookshelves

Location Recognition in RFID Bookshelves

RSSI-based indoor tracking using the extended Kalman filter and circularly polarized antennas

Effect of primary power fluctuation on ergodic capacity of a secondary user in a spectrum sharing environment

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