Fuzzy-Based Indoor Positioning by Using the Neighbor Points

Abstract

This paper presents a fuzzy-based indoor positioning system (IPS) by using the information of neighbor points to estimate the location of object. An 8x8 square meters indoor area was used as the experimental area. In the experimental field, the received signal strength (RSS) of 288 points, 392 points, 440 points and 704 points were sensed and collected by a hexagonal positioning station which is composed of six printed-circuit board SPARKLAN AX-106M antennas and Zigbee module. The sensed RSS values are then used to be the information of fuzzy system for the object's position estimation. From the experimental results shown, the proposed IPS and fuzzy estimation method do have the accurate positioning performance and indeed has the potential in the real application.

Sparklan Antenna in Indoor Positioning Application

“…However, only the 10 closest neighbor points with the closest RSS signals between the reference and blind nodes are used for the positioning estimation in all the tests. (21) Tables 2 and 3 show some of the estimated mean absolute errors (MAEs) for 288 and 392 test points, respectively. From the experimental results shown, the positioning performance of the developed IPS is clearly found to be still good even when some of the antennas fail.…”

“…The detailed fuzzy estimation process is presented as follows. (20,21) Now, we assume that the RSS signals sensed at a blind node (x b , y b ) are (r 1b , r 2b , r 3b , r 4b , r 5b , r 6b ) and that the fuzzy rule is constructed using the m fuzzy IF-THEN rules expressed as follows.…”