Concept of Detection System to Localize Inside Closed Area by Radio Tomographic Imaging

Rymarczyk, Tomasz; Adamkiewicz, Przemysław; Szumowski, Jakub; Niderla, Konrad; Gołąbek, Łukasz; Sikora, J.

doi:10.5604/01.3001.0010.4592

Cited by 2 publications

(1 citation statement)

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“…One of the primary uses are attempts to locate an object (device) on the basis of received signal strength indicator (RSSI). Many papers describe the use of RSSI for indoor location [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ] and outdoor location [ 8 , 9 , 10 , 11 , 12 , 13 ]. The main reason for these applications is the wide availability and affordability of devices using the received signal strength indicator.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Path-Loss Exponent by Bayesian Filtering Method

Wójcicki

Zientarski

Charytanowicz

et al. 2021

Sensors

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Regarding wireless sensor network parameter estimation of the propagation model is a most important issue. Variations of the received signal strength indicator (RSSI) parameter are a fundamental problem of a system based on signal strength. In the present paper, we propose an algorithm based on Bayesian filtering techniques for estimating the path-loss exponent of the log-normal shadowing propagation model for outdoor RSSI measurements. Furthermore, in a series of experiments, we will demonstrate the usefulness of the particle filter for estimating the RSSI data. The stability of this algorithm and the differences in determined path-loss exponent for both method were also analysed. The proposed method of dynamic estimation results in significant improvements of the accuracy of RSSI values when compared with the experimental measurements. It should be emphasised that the path-loss exponent mainly depends on the RSSI data. Our results also indicate that increasing the number of inserted particles does not significantly raise the quality of the estimated parameters.

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