Errata: High precision three-dimensional iterative indoor localization algorithm using code division multiple access modulation based on visible light communication

Guan, Weipeng; Wu, Yuxiang; Wen, Shangsheng; Yang, Chen Ning; Chen, Hao; Zhang, Zhaoze; Chen, Ying-Cong

doi:10.1117/1.oe.55.11.119801

Cited by 3 publications

(2 citation statements)

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“…) =1 (13) According to the relationship of linear transition, the average value of the noise component sequence of the interfered link based on the state transition probability is:…”

Section: Linear Transition Model Of State Transition Probabilitymentioning

confidence: 99%

“…Six LEDs are located in A (0.15,0.15,0.6), B (0.15,0.55,0.6), C (0.15,0.95,0.6), D (0.95,0.15,0.6), E (0.95,0.55,0.6) and F (0.95,0.95,0.6). LED-ID [12][13][14] technology is used in positioning systems to enable the receiver to distinguish signal strength from different LEDs. In the real environment, the LEDs send the signal with a certain duty cycle, which is received by the photodetector.…”

Section: Analysis and Verificationmentioning

confidence: 99%

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Indoor Visible Light Localization Based on Finite State Markov Chain

Shen

Shao

Deng

et al. 2021

Preprint

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In the study of indoor visible light localization, the variance of the RSS(Received Signal Strength) distribution will be affected by environmental noise, resulting in a larger range of RSS value fluctuations. A method is proposed to decompose the RSS value into the disturbance component caused by the target and the noise component caused by the environment, and then a linear transfer model based on the finite state Markov chain is used to extract the disturbance component in RSS value. Finally, the DTW(Dynamic Time Warping) algorithm is used to match the real-time disturbance component with the fingerprint database to achieve target positioning.

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“…) =1 (13) According to the relationship of linear transition, the average value of the noise component sequence of the interfered link based on the state transition probability is:…”

Section: Linear Transition Model Of State Transition Probabilitymentioning

confidence: 99%

Section: Analysis and Verificationmentioning

confidence: 99%

Indoor Visible Light Localization Based on Finite State Markov Chain

Shen

Shao

Deng

et al. 2021

Preprint

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show abstract

Indoor visible light localization based on compressed sensing under matrix filling recovery

et al. 2020

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Improved Target Signal Source Tracking and Extraction Method Based on Outdoor Visible Light Communication Using a Cam-Shift Algorithm and Kalman Filter

Huang

Guan

Fan

et al. 2018

Sensors

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An improved Cam-Shift algorithm with a Kalman filter applied to image-sensor based on outdoor visible light communication (OVLC) is presented in this paper. The proposed optimized tracking algorithm is used to track and extract the region of the target signal source Light Emitting Diode (LED) that carries modulated information for data transmission. Extracting the target signal source LED area is the premise of an image-sensor-based VLC system, especially in outdoor dynamic scenes. However, most of the existing VLC studies focus on data transmission rate, visible light positioning, etc. While the actual first step of realizing communication is usually ignored in the field of VLC, especially when the transmitter (signal source LED) or the receiver (image sensor) is moving in a more complex outdoor environment. Therefore, an improved tracking algorithm is proposed in this paper, aiming at solving the problem of extracting the region of the target signal source LED accurately in dynamic scenes with different interferences so as to promote the feasibility of VLC applications in outdoor scenes. The proposed algorithm considers color characteristics and special distribution characteristics of the moving target at the same time. The image is converted to a color probability distribution map based on the color histogram of the target and adaptively adjusts the location and size of the search window based on the results obtained from the previous frame. Meanwhile, it predicts the motion state of the target in the next frame according to the position and velocity information of the current frame to enhance accuracy and robustness of tracking. Experimental results show that the tracking error of the proposed algorithm is 0.85 cm and the computational time of processing one frame is 0.042 s. Besides, results also show that the improved algorithm can track and extract the target signal source LED area completely and accurately in an environment of many interference factors. This study confirms that the proposed algorithm can be applied to an OVLC system with many interferences to realize the actual first step of communication in an image-sensor-based VLC system, laying foundations for subsequent data transmission and other steps.

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Errata: High precision three-dimensional iterative indoor localization algorithm using code division multiple access modulation based on visible light communication

Abstract: "Errata: High precision three-dimensional iterative indoor localization algorithm using code division multiple access modulation based on visible light communication,"

Cited by 3 publications

References 0 publications

Indoor Visible Light Localization Based on Finite State Markov Chain

Indoor Visible Light Localization Based on Finite State Markov Chain

Indoor visible light localization based on compressed sensing under matrix filling recovery

Improved Target Signal Source Tracking and Extraction Method Based on Outdoor Visible Light Communication Using a Cam-Shift Algorithm and Kalman Filter

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