IMPROVED INDOOR POSITIONING USING FINGERPRINT TECHNIQUE AND WEIGHTED K-NEAREST NEIGHBOUR

Abstract. Global Navigation Satellite Systems are not effective when there is no direct line of sight between the user and satellites, such as indoor environments dense urban areas. Today, location-based services used significantly due to their utility ease access. The fingerprint method one common methods determining location in environments. In this research, positioning system based on algorithm with a wireless network has been implemented. nearest neighbour weighted K-nearest two access points implemented different scenarios. output accuracy each technique compared other. main goal article compare using mentioned algorithms find most suitable mode for position places. improved will have an almost acceptable result all scenarios also first scenario regular reference RMSE=0.2812(m) provided best result. second scattered irregular RMSE=0.6735(m) given lower