In this thesis, an indoor positioning system based on iBeacon and phone sensors was presented. In this thesis, we propose a realtime indoor positioning system in smartphone via BLE iBeacon signal. In which, we used embedded sensors for displacement calculation and BLE iBeacon signal as a calibrated opportunity for sensorbased IPS. Firstly, we investigate the problems associated with the uncertainty of RSS, then offer solution for RSSbased locating moving target under low sampling rate. Secondly, we proposed method of improving accuracy for LSE method. Improved LSEbased position then fused with PDRbased position using Kalman filter to produce more accurate positions. The accuracy of the proposed approaches proved high persuasion for service providers to deploy this lowcomplexity system for various locationbased services In this thesis, an indoor positioning system based on iBeacon and phone sensors was presented. In this thesis, we propose a realtime indoor positioning system in smartphone via BLE iBeacon signal. In which, we used embedded sensors for displacement calculation and BLE iBeacon signal as a calibrated opportunity for sensorbased IPS. Firstly, we investigate the problems associated with the uncertainty of RSS, then offer solution for RSSbased locating moving target under low sampling rate. Secondly, we proposed method of improving accuracy for LSE method. Improved LSEbased position then fused with PDRbased position using Kalman filter to produce more accurate positions. The accuracy of the proposed approaches proved high persuasion for service providers to deploy this lowcomplexity system for various locationbased services