• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm

Vol. 3, No.1, February 23, 2009
10.3837/tiis.2009.01.007, Download Paper (Free):

Abstract

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.


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Cite this article

[IEEE Style]
Sung-Hak Song, Chang-Hoon Lee, Ju-Hyun Park, Kyo-Jun Koo, Jong-Kook Kim and Jongsun Park, "Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm," KSII Transactions on Internet and Information Systems, vol. 3, no. 1, pp. 119-133, 2009. DOI: 10.3837/tiis.2009.01.007

[ACM Style]
Song, S., Lee, C., Park, J., Koo, K., Kim, J., and Park, J. 2009. Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm. KSII Transactions on Internet and Information Systems, 3, 1, (2009), 119-133. DOI: 10.3837/tiis.2009.01.007