Indoor location estimation based on the RSS method using radial log-normal distribution

Okusa, Kosuke; Kamakura, Toshinari

doi:10.1109/cinti.2015.7382938

Cited by 6 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Researchers in [3] explain indoor location estimation based on the RSS algorithm using radial log-normal distribution. The researchers estimate the location of the object using marginal likelihoods of the radial lognormal distribution.…”

Section: Introductionmentioning

confidence: 99%

Impact of The Number of Light Emitting Diode Towards The Accuracy in Indoor Positioning System Based on Visible Light Communication

Pamukti

Rahmawati

Adriansyah

2020

indones.j.electron.telecommun.

View full text Add to dashboard Cite

This research detects the random position with received signal strength (RSS) method based on the received power in the room with a size of 5×5×3 cubic meter and several numbers of light emitting diode (LEDs). The first scenario uses 4 LEDs, the second scenario uses 6 LEDs and the third scenario uses 8 LEDs. Random points as the detector are placed spread at the room as many as 25 points. The simulation result shows that the use of more LEDs reduces the positioning error and increases the accuracy. If the accuracy reduces, the positioning error increase and affect the detection results. Using 8 LEDs, the number of the detected random point increases 30%, the positioning error is 47%, and the accuracy increase from 33%. In addition, our research is useful for finding the locations of small items such as sensors that are scattered in a closed room.

show abstract

Section: Introductionmentioning

confidence: 99%

Impact of The Number of Light Emitting Diode Towards The Accuracy in Indoor Positioning System Based on Visible Light Communication

Pamukti

Rahmawati

Adriansyah

2020

indones.j.electron.telecommun.

View full text Add to dashboard Cite

show abstract

“…For measuring distance, there are various kinds of radio signal information to measure a distance, such as Received Signal Strength (RSS) (Okusa and Kamakura, 2015), Time-of-Arrival (ToA) (Kamakura and Okusa, 2013;Venkatraman, Caffery and You, 2004;Watabe and Kamakura, 2010), and Angle-of-Arrival (AoA). We have to select or combine these sources of information to estimate the position of TAG.…”

Section: Introductionmentioning

confidence: 99%

Indoor Location Estimation Based on Toa Data and Bias Estimation Using Gamma Regression

Yoshida

Sakumura

Kamakura

2018

Journal of the Japanese Society of Computational Statistics

Self Cite

View full text Add to dashboard Cite

We aim at improving the accuracy of indoor position estimation through a statistical approach. In this study, we propose a position estimation method based on Time-of-Arrival (ToA). ToA data are often useful. However, ToA data include a positive bias due to the reflection of radio waves. Therefore, it is difficult to estimate the TAG position from ToA data directly without an accurate bias correction. In this paper, we propose a maximum likelihood estimation method for the TAG position using gamma regression and a rotated distribution, and we show that the estimation with bias correction is more accurate than the estimation without bias correction. In addition, we show that our method also provides a confidence region for the TAG position.

show abstract

A Simulation Study on Indoor Location Estimation Based on the Extreme Radial Weibull Distribution

Okusa

Kamakura

2018

Transactions on Engineering Technologies

View full text Add to dashboard Cite

Indoor location estimation based on the RSS method using radial log-normal distribution

Cited by 6 publications

References 19 publications

Impact of The Number of Light Emitting Diode Towards The Accuracy in Indoor Positioning System Based on Visible Light Communication

Impact of The Number of Light Emitting Diode Towards The Accuracy in Indoor Positioning System Based on Visible Light Communication

Indoor Location Estimation Based on Toa Data and Bias Estimation Using Gamma Regression

A Simulation Study on Indoor Location Estimation Based on the Extreme Radial Weibull Distribution

Contact Info

Product

Resources

About