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The recent growing interest for RFID based localization has created a need for easier installation and more accurate for indoor positioning. The CAA (Cylindrical Antennas Array) that consists of twelve directional antennas has been developed in this paper. In the area covered by directional antennas, only one antennas array is needed to locate the tags with the proposed method. Based on the designed system, the paper proposed a fingerprint-based localization with the aid of IMU (Inertial Measurement Unit), which is used to assist the filtering of received RF data and get the knowledge of the efficiency of current fingerprint database (radio map). In addition, the received data vectors by CAA have twelve dimensions which could improve the fingerprint-based localization accuracy. The experiments were conducted with the proposed system to position the tags and make a comparison with other indoor localization methods. The result shows it could increase the positioning accuracy of tags and enhanced the performance of RSS-based fingerprint localization. 1

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“…Radio-maps can be generated either through measurements or theoretically through simulations [2], [4], [5], [6], [7].…”

Section: A Radio-map Generation Methodologiesmentioning

confidence: 99%

“…, l, with l being the number of fingerprints in the radio-map. Probabilistic algorithms have been used in the Maximum A Posteriori (MAP) [13] and Minimum Mean Square Error (MMSE) [6] approaches.…”

Section: B Rss Fingerprint-based Positioning Algorithmsmentioning

confidence: 99%

Improving RSS fingerprint-based localization using directional antennas

Kanaris

Kokkinis

Raspopoulos

et al. 2014

The 8th European Conference on Antennas and Propagation (EuCAP 2014)

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“…In this work we used kernel function approximation, because, according to the numerous surveys, this method gives more accurate results [1]. In general, the a priori function is uniform and posterior distribution of location depends only of likelihood function.…”

Section: A Fingerprinting Techniquementioning

confidence: 99%

“…According to [1] the prior pdf can be constructed by  map matching (MU cannot jump from one room to another, the number of the next possible locations is restricted)…”

Section: B Predictionmentioning

confidence: 99%

See 1 more Smart Citation

A hybrid localization technique for patient tracking

Rodionov

Kolev²,

Bushminkin

2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Nowadays numerous technologies are employed for tracking patients and assets in hospitals or nursing homes. Each of them has advantages and drawbacks. For example, WiFi localization has relatively good accuracy but cannot be used in case of power outage or in the areas with poor WiFi coverage. Magnetometer positioning or cellular network does not have such problems but they are not as accurate as localization with WiFi. This paper describes technique that simultaneously employs different localization technologies for enhancing stability and average accuracy of localization. The proposed algorithm is based on fingerprinting method paired with data fusion and prediction algorithms for estimating the object location. The core idea of the algorithm is technology fusion using error estimation methods. For testing accuracy and performance of the algorithm testing simulation environment has been implemented. Significant accuracy improvement was showed in practical scenarios.

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Node Localization

and

Pahlavan

2008

Wireless Sensor Networks

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Cited by 689 publications

References 15 publications

Improving RSS fingerprint-based localization using directional antennas

Improving RSS fingerprint-based localization using directional antennas

A hybrid localization technique for patient tracking

Node Localization

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