Abstract
Ubiquitous indoor environments often contain substantial amounts of metal and other similar reflective materials that affect the propagation of radio frequency signals in important ways, causing severe multipath effects, including noise and interference, when measuring the signal strength between sender and receiver. To minimize the noise level, this study proposes advanced fusion filter (AFF) and improved fusion filter (IFF) using received signal strength indicator (RSSI) and link quality indicator (LQI) by using feedback filter. The aim of this research was to provide a low cost, simple technique based on RSSI and LQI values, provided by ZigBee module without considering needs to change the system according to specific indoor environments. The proposed technique could efficiently decrease huge amount of noise level from the original signal. To check the performance of the proposed technique, this study applied median filter and Savitzky-Golay filter to compare the performance of AFF and IFF. Further, the statistical analysis technique of cross-correlation method was used to check the similarity between original signal and filtered signal. The simulation results demonstrate the efficiency of the proposed RF-based indoor location determination.
Highlights
Indoor localization systems have gained a significant attention in recent years due to their ease of deployment, low cost, and potential applications in several areas
In order to measure a more accurate range, this paper proposes two new filtering techniques, advanced fusion filter (AFF) and improved fusion filter (IFF), which effectively eliminate the noises by providing exponential α value to the acquired data in consideration of the signal attenuation characteristics of the received signal strength indicator (RSSI), which has a log distribution
It was verified that the proposed AFF and IFF, fusion, RSSI, and link quality indicator (LQI) filters were sequentially excellent in the noise elimination performance in three paths
Summary
Indoor localization systems have gained a significant attention in recent years due to their ease of deployment, low cost, and potential applications in several areas. Received signal strength indicator (RSSI) is affected by the distance between the nodes but there are few other factors that affect the radio signal propagation and the RSSI value that is perceived by a node. The localization systems presented in this study are based on the RSSI as a strength indicator and LQI as a quality indicator of a received packet and can be used to estimate a distance from a node to reference points. This scheme can find out the location of the object by measuring the RSSI and LQI according to distance.
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