Wireless Positioning Algorithm Based on RSS in Limited Space

Wang, Yongxing; Hua, Gang; Yong-gang, XU; Yin, Hongsheng

doi:10.14257/ijsip.2016.9.1.32

Cited by 3 publications

(3 citation statements)

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“…Under the second order stationary hypothesis, the autocorrelation between () Rl and () R l h  does not depend on the actual position l ; it only depends on the displacement between the two parts, so the following Equation (12) can be obtained. Thus, an estimate of the expression of the variance function can be deduced [24], as shown in Equation (13).…”

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confidence: 99%

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Position of Fingerprint Location based on Improved Universal Kriging Interpolation Method

Wang¹,

Ge²,

Duan³

et al. 2019

Int J Performability Eng

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The accuracy of fingerprint databases is very important to position fingerprint locations. However, due to the measurement of the received signal strength cost and artificial constraints, the measured RSSI is limited, resulting in insufficient accuracy of fingerprint databases. Therefore, we adopt the spatial interpolation algorithm to obtain a more accurate location fingerprint database and innovatively propose an improved universal Kriging interpolation method, introducing variable parameters, overcoming the shortcomings of large measurement errors in the variation function, and generating an accurate location fingerprint database. The simulation results show that compared with the universal Kriging interpolation method and the inverse distance weighting method, the standard error of prediction is increased by 76.33% and 96.50%, respectively.

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confidence: 99%

“…The accuracy of the fingerprint database directly affects the accuracy of the positioning results to a large extent. The establishment of high-precision fingerprint databases is a prerequisite for highprecision positioning results [9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Position of Fingerprint Location based on Improved Universal Kriging Interpolation Method

Wang¹,

Ge²,

Duan³

et al. 2019

Int J Performability Eng

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“…Common wireless positioning algorithms include those based on the received signal strength indicator (RSSI), the angle of arrival (AOA), the time of arrival (TOA), and the time difference of arrival (TDOA) [3][4][5][6] . For relatively closed environments (e.g., transmission pipe gallery), electromagnetic and acoustic wave signals introduce strongly reflected interference; thus, the RSSI and AOA algorithms are ineffective.…”

Section: Introductionmentioning

confidence: 99%

Wireless positioning method for transmission pipe gallery inspection robot based on the TDOA algorithm

Yao,

Zhang,

Luo

et al. 2023

J. Phys.: Conf. Ser.

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A wireless sensor network for positioning an inspection robot is developed for a transmission pipe gallery environment. The time difference of the arrival algorithm optimized by the least squares method is utilized to realize the wireless positioning function of the robot in the inspection process. The developed system adopts a spiral configuration to install the sensor nodes at equal intervals on the sidewall of the transmission pipe gallery, and only 10 sensor nodes closest to the wireless signal transmission source are activated for each measurement, which avoids the poor long-distance measurement effect of the sensor, ensures sufficient accuracy, and reduces calculation costs. A wireless positioning simulation test was conducted in an experimental transmission corridor environment. The error of the simulation results is equivalent to the measurement error of a single sensor, and the error is not accumulated in the calculation of the algorithm, indicating that the algorithm has achieved good results.

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