Advanced smoothing approach of RSSI and LQI for indoor localization system

Sharly Joana Halder, Paritosh Giri, Wooju Kim*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)
9 Downloads (Pure)


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.

Original languageEnglish
Article number195297
Number of pages11
JournalInternational Journal of Distributed Sensor Networks
Issue number5
Publication statusPublished - 1 Jan 2015
Externally publishedYes

Bibliographical note

Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • Filters
  • Signal processing
  • ZigBee
  • wireless communication
  • Received Signal Strength Indicator (RSSI)
  • link quality


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