Method for efficiently constructing and updating radio map of fingerprint positioning

Liu, Xingchuan; Zhang, Sheng; Lu, Henghui; Lin, Xiao

doi:10.1109/glocomw.2010.5700423

Cited by 9 publications

(6 citation statements)

References 14 publications

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“…These results are very similar or even slightly better than the results reported in the former papers [13,16,17,18,19]. Our approach has the advantage of not depending on offline training data, which enables it to automatically constructed the positioning system and dynamically model the changes in the environment.…”

Section: Experiments Sectionsupporting

confidence: 86%

“…Nevertheless, this simple idea produces inaccurate radio maps, which decrease the accuracy of the location estimation. Consequently, many other attempts have been proposed, including the free-calibration methods [13,14,15,16,17,18,19,20], user-aided methods [21,22] and the auto-update technologies [23]. …”

Section: Introductionmentioning

confidence: 99%

“…Besides the training signal path loss models [16], the interpolation and regression technologies [17,18,19] have also been widely used. A micro-cell-based map construction method is proposed in [20] to deal with the unstable RSSI and build a metropolitan-scale radio map efficiently.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower

Yang

Xiu

2015

Sensors

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With the rapid development of WIFI technology, WIFI-based indoor positioning technology has been widely studied for location-based services. To solve the problems related to the signal strength database adopted in the widely used fingerprint positioning technology, we first introduce a new system framework in this paper, which includes a modified AP firmware and some cheap self-made WIFI sensor anchors. The periodically scanned reports regarding the neighboring APs and sensor anchors are sent to the positioning server and serve as the calibration points. Besides the calculation of correlations between the target points and the neighboring calibration points, we take full advantage of the important but easily overlooked feature that the signal attenuation model varies in different regions in the regression algorithm to get more accurate results. Thus, a novel method called RSSI Geography Weighted Regression (RGWR) is proposed to solve the fingerprint database construction problem. The average error of all the calibration points’ self-localization results will help to make the final decision of whether the database is the latest or has to be updated automatically. The effects of anchors on system performance are further researched to conclude that the anchors should be deployed at the locations that stand for the features of RSSI distributions. The proposed system is convenient for the establishment of practical positioning system and extensive experiments have been performed to validate that the proposed method is robust and manpower efficient.

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Section: Experiments Sectionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

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A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower

Yang

Xiu

2015

Sensors

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“…The conventional way of creating fingerprint training data-base is to periodically conduct extensive drive test campaigns which are time-consuming and unpractical for building a metropolitan-scale radio map of the locating system [41], [12]. A major drawback of this method is to update the training radio map when new APs are deployed and existing APs are decommissioned.…”

Section: Rf Fingerprint Collection and Updatingmentioning

confidence: 99%

Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Signal Strengths

Mondal

Ristaniemi

Turkka³

2017

Int J Wireless Inf Networks

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Wireless Local Area Network (WLAN) positioning has become a popular localization system due to its low-cost installation and widespread availability of WLAN access points (AP). Traditional grid-based radio frequency (RF) fingerprinting (GRFF) suffers from two drawbacks. First it requires costly and non-efficient data collection and updating procedure; secondly the method goes through time-consuming data pre-processing before it outputs user position. This paper proposes Cluster-based RF Fingerprinting (CRFF) to overcome these limitations by using modified Minimization of Drive Tests (MDT) data which can be autonomously collected by cellular operators from their subscribers. The effect of environmental changes and device variation on positioning accuracy has been carried out. Experimental results show that even under these variations CRFF can improve positioning accuracy by 15.46% and 22.30% in 95 percentile of positioning error (PE) as compared to that of GRFF and K-nearest neighbour methods respectively.

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“…The establishment of fingerprint space determines the positioning range and positioning accuracy of Location Fingerprinting. Since the interpolation can reduce the number of sampling points, improve the efficiency of fingerprint space building and ensure the positioning accuracy, it becomes one of the research focuses on extending positioning range [3] [4] . The major existing interpolation method to establish fingerprint space is the traditional Kriging [5] , log-propagation path loss model [6] [7] and the weighted distance inverse IDW [8] .The former two methods do not consider the relationship of sampling points, ignore the influences of the entire fingerprint spatial sampling points towards the measuring point correlation, resulting in lower interpolation accuracy.…”

Section: Introductionmentioning

confidence: 99%

Fingerprint Space Building Algorithm with Kriging for Large Positioning Regional Environment

Wang¹,

Cui²,

Wang³

et al. 2015

Advances in Computer Science Research

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When using the arithmetic of location fingerprinting to build up fingerprint spaces, the methodology that scholars used now contains drawbacks, such as the high complexity and low accuracy and other iuess. As a result, Kriging are using frequently. In the traditional style, chosen Kriging index could only be applied to empirical models for small-scaled indoor scenes. Therefore, proposes to use least-square fitting based variogram model to obtain the theoretical model of related parameters for large targeted area environment. Result of this experiment shows that the new method can improve the fitting degree. Supposing the space of samples is 5-25 meters, the interpolation accuracy enhanced by 0.17dB-0.45dB, positioning accuracy positioning accuracy are enhanced by 0.4m-1.47m as well compared with existing techniques.

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Method for efficiently constructing and updating radio map of fingerprint positioning

Cited by 9 publications

References 14 publications

A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower

A Novel Method for Constructing a WIFI Positioning System with Efficient Manpower

Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Signal Strengths

Fingerprint Space Building Algorithm with Kriging for Large Positioning Regional Environment

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