A Study of Intelligent Algorithms for Indoor Positioning

• Main Authors: Guang-Jeng Tseng, 曾光正
• Other Authors: 陳智勇
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/39123157260870305789

碩士 === 樹德科技大學 === 電腦與通訊系碩士班 === 98 === In this thesis, the Zigbee wireless sensors network will be applied to be the basis of the proposed system, and then the distance will be measured by received signal strength (RSS) between devices. One-dimensional spatial filter is designed to obtain a more accurate signal strength information. Subsequently, apply COA Solutions in three different evolutionary algorithms, such as particle swarm optimizer (PSO), fuzzy theory and the modified probabilistic neural network (MPNN) to be the indoor positioning engine to calculate the object coordinates. Diverse experiments and simulations are performed to analyze and compare the performance of robustness for the proposed different methods. The experiments demonstrate that the proposed methods is this thesis are with higher accuracy and robustness than triangulation technique.