On the RBF-based positioning using WLAN signal strength fingerprints

Laoudias, Christos; Panayiotou, Christos G.; Kemppi, Paul

doi:10.1109/wpnc.2010.5653403

Cited by 20 publications

(4 citation statements)

References 13 publications

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“…Even though, the authors showed a promising effort-reduction method, further investigation in this method is still required. Furthermore, in [8][9][10] the problem of real-time APs selection for WLAN positioning has been addressed. The authors in [8] proposed an algorithm that uses parametric and nonparametric divergence measures for selecting only subset of the available APs, within the positioning area, to be used for position estimation.…”

Section: Related Workmentioning

confidence: 99%

“…The authors in [8] proposed an algorithm that uses parametric and nonparametric divergence measures for selecting only subset of the available APs, within the positioning area, to be used for position estimation. Also the authors in [9] incorporated the RSSI measurements into the estimation method and couple that with a methodology that indicates which of the detected APs can be ignored during positioning without degradation on the overall position accuracy. Both methods were proposed to reduce the impact on the computational complexity of the positioning algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…For each value we generated separate Calibration and Testing Sets. We have chosen these values based on the results presented in [9]. The authors presented experimental results to illustrate the variation on the RSSI values of a single AP for two different collecting setups over a period of 10 hours.…”

Section: B Data Preprocessingmentioning

confidence: 99%

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Removing useless APs and fingerprints from WiFi indoor positioning radio maps

Eisa

Peixoto

Meneses

et al. 2013

International Conference on Indoor Positioning and Indoor Navigation

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Maintaining consistent radio maps for WiFi fingerprinting-based indoor positioning systems is an essential step to improve the performance of the positioning engines. The radio maps consist of WiFi fingerprints collected at a predefined set of positions/places within a positioning area. Each fingerprint consists of the identification and radio signal level of the surrounding Access Points (APs). Due to the wide proliferation of WiFi networks, it is very common to observe 10 to 20 APs at a single position and more than 50 APs across a single building. However, in practical, not all of the detected APs are useful for the position estimation process. Some of them might have weak signals at certain positions or might have less significance for a position's fingerprint. Thus, those useless APs will add additional computational overheads during the position estimation, and consequently they will reduce the overall performance of the positioning engines. A similar phenomenon also occurs with some of the collected fingerprints. While it is widely accepted that the larger and more detailed the radio map is, the better is the accuracy of the positioning system, we found that some of the fingerprint samples on the radio maps do not contribute significantly to the estimation process. In this paper, we propose two methods for filtering the positioning radio maps: APs filtering and Fingerprints filtering. Then we report on the results of a set of experiments that have been done to evaluate the performance of a WiFi positioning radio map before and after applying the filtering approaches. The results show that there is possibility to simplify the radio maps of the positioning engines without significant degradation on the positioning precision and accuracy, and therefore to reduce the processing time for estimating the position of a tracked WiFi tag. This result has an important impact on increasing the number of tags a single instance of a WiFi positioning engine can handle at a time.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Removing useless APs and fingerprints from WiFi indoor positioning radio maps

Eisa

Peixoto

Meneses

et al. 2013

International Conference on Indoor Positioning and Indoor Navigation

View full text Add to dashboard Cite

show abstract

“…Several researches on fingerprint positioning focus on reducing the fingerprint dimension to lessen the positioning overhead. The researchers in [36,37] aim to reduce the number of available APs that can be used for the positioning purpose. In [38], some clustering strategy and decision tree method are applied to choose an optimum set of APs to reduce the computational power and positioning overhead.…”

Section: Related Workmentioning

confidence: 99%