Robust Indoor Positioning Based on Received Signal Strength

Published

July 10, 2007

Author(s)

Kamran Sayrafian, Julio Perez

Abstract

RF-based indoor positioning is a challenging task due to the harsh indoor propagation environment. Techniques based on the received signal strength are simple to implement and offer low cost and effective alternatives for some applications. The main drawback of such techniques is the need for a measurement-based training phase, during which a `Radio Map' of the environment is created. The process to generate a radio map is not only labor-intensive but also very sensitive to possible changes in the environments. While maintaining the simplicity of an RSS-based positioning system, the objective of this paper is to investigate a methodology that helps to eliminate this training phase and its impact on the achieved performance. For this purpose, we will discuss a positioning algorithm based on the relative order of the received signal strengths that in conjunction with the ray-tracing propagation model can have promising performance for indoor environments without any needs for extensive set of a priori training. Enhancements to the positioning algorithm will be proposed and investigated. Two sets of experimental results with 802.11-based infrastructure and MICA2 motes are presented to demonstrate the system capability and performance in practice.

Proceedings Title

International Conference on Pervasive Computing and Applications | 2nd | 2007 | |

Conference Dates

July 26-27, 2007

Conference Location

Birmingham, UK

Conference Title

Second International Conference on Pervasive Computing and Applications

Pub Type

Conferences

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Keywords

Indoor Positioning, Ray-Tracing, RF Signal Strength

Citation

Sayrafian, K. and Perez, J. (2007), Robust Indoor Positioning Based on Received Signal Strength, International Conference on Pervasive Computing and Applications | 2nd | 2007 | |, Birmingham, UK, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=51180 (Accessed October 6, 2024)