Enhancing location estimation and reducing computation using adaptive zone based K-NNSS algorithm

Sung Hak Song, Chang Hoon Lee, Ju Hyun Park, Kyo Jun Koo, Jong Kook Kim, Jongsun Park

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

Original languageEnglish
Pages (from-to)119-133
Number of pages15
JournalKSII Transactions on Internet and Information Systems
Issue number1
Publication statusPublished - 2009


  • K-NNSS
  • Location estimation
  • Location tracking
  • Location-based-Service
  • WLAN

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications


Dive into the research topics of 'Enhancing location estimation and reducing computation using adaptive zone based K-NNSS algorithm'. Together they form a unique fingerprint.

Cite this