Beacon based indoor positioning system using weighted centroid localization approach

Subedi, Santosh; Kwon, Goo‐Rak; Shin, Seokjoo; Hwang, Suk-Seung; Pyun, Jae-Young

doi:10.1109/icufn.2016.7536951

Cited by 51 publications

(37 citation statements)

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“…Some typical values of g are 0.5, 1, and 2.6 [2,3,8]. For example, Figure 1 illustrates WCL with three beacons within the localization area.…”

Section: Weighted Centroid Localization (Wcl)mentioning

confidence: 99%

“…However, the inevitable drawback of this method is the requirement of a tedious and time-consuming offline phase. Also, though WCL seems easy and flexible to implement, it has a high localization error [2]. The proposed system starts with the removal of noisy RSSI values followed by the proposed positioning method explained below.…”

Section: The Proposed Positioning Systemmentioning

confidence: 99%

“…where (x w , y w ) is the estimated coordinate of the WCL method, d i is distance between the tag and beacon i, g is the degree of weight [2], and m is the total number of beacons considered at any time for location estimation. Some typical values of g are 0.5, 1, and 2.6 [2,3,8].…”

Section: Weighted Centroid Localization (Wcl)mentioning

confidence: 99%

“…Distance Observation from RSSI. After the RSSI estimation, it is converted to distance using the following relation between distance and received power [2,23].…”

Section: Moving Average Filter For Smoothing Rssi As Shown Inmentioning

confidence: 99%

“…The weighted centroid localization (WCL) method can also be a candidate technology for IPS. WCL is known as flexible, easy to implement, and consumes less time, but it has a large location estimation error [2,3].…”

Section: Introductionmentioning

confidence: 99%

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Practical Fingerprinting Localization for Indoor Positioning System by Using Beacons

Subedi

Pyun

2017

Journal of Sensors

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Recent developments in the fields of smartphones and wireless communication technologies such as beacons, Wi-Fi, and ultrawideband have made it possible to realize indoor positioning system (IPS) with a few meters of accuracy. In this paper, an improvement over traditional fingerprinting localization is proposed by combining it with weighted centroid localization (WCL). The proposed localization method reduces the total number of fingerprint reference points over the localization space, thus minimizing both the time required for reading radio frequency signals and the number of reference points needed during the fingerprinting learning process, which eventually makes the process less time-consuming. The proposed positioning has two major steps of operation. In the first step, we have realized fingerprinting that utilizes lightly populated reference points (RPs) and WCL individually. Using the location estimated at the first step, WCL is run again for the final location estimation. The proposed localization technique reduces the number of required fingerprint RPs by more than 40% compared to normal fingerprinting localization method with a similar localization estimation error.

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“…Some typical values of g are 0.5, 1, and 2.6 [2,3,8]. For example, Figure 1 illustrates WCL with three beacons within the localization area.…”

Section: Weighted Centroid Localization (Wcl)mentioning

confidence: 99%

Section: The Proposed Positioning Systemmentioning

confidence: 99%

Section: Weighted Centroid Localization (Wcl)mentioning

confidence: 99%

“…Distance Observation from RSSI. After the RSSI estimation, it is converted to distance using the following relation between distance and received power [2,23].…”

Section: Moving Average Filter For Smoothing Rssi As Shown Inmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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