Supporting Node Connectivity with Dixon’s Test for ZigBee-based WSN

Yoo, S W; Wang, Cheng; Kim, Young Ho; Kim, Sejun; Youn, Hee Yong

doi:10.1016/j.procs.2018.10.152

Cited by 1 publication

(1 citation statement)

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“…In indoor distance measurement, the distance measurement method based on ZigBee [6][7][8] has received widespread attention due to its advantages of low power consumption, low cost, and easy deployment. However, the existing ZigBee indoor distance measurement method has problems such as low distance measurement accuracy, large positioning error, poor robustness, etc., which limits its promotion and application in practical applications.…”

Section: Introductionmentioning

confidence: 99%

A Combined Filtering Method for ZigBee Indoor Distance Measurement

Wei,

Zhou

2024

Sensors

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Indoor distance measurement technology utilizing Zigbee’s Received Signal Strength Indication (RSSI) offers cost-effective and energy-efficient advantages, making it widely adopted for indoor distance measurement applications. However, challenges such as multipath effects, signal attenuation, and signal blockage often degrade the accuracy of distance measurements. Addressing these issues, this study proposes a combined filtering approach integrating Kalman filtering, Dixon’s Q-test, Gaussian filtering, and mean filtering. Initially, the method evaluates Zigbee’s transmission power, channel, and other parameters, analyzing their impact on RSSI values. Subsequently, it fits a signal propagation loss model based on actual measured data to understand the filtering algorithm’s effect on distance measurement error. Experimental results demonstrate that the proposed method effectively improves the conversion relationship between RSSI and distance. The average distance measurement error, approximately 0.46 m, substantially outperforms errors derived from raw RSSI data. Consequently, this method offers enhanced distance measurement accuracy, making it particularly suitable for indoor positioning applications.

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Section: Introductionmentioning

confidence: 99%