Indoor Localization for Wireless Sensor Networks

• Main Authors: Shi-Huang Pan, 潘思黃
• Other Authors: Ren C. Luo
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/57645601907867943586

碩士 === 國立中正大學 === 電機工程所 === 93 === Knowing the position of mobile user is an important role for location services in the building. The characteristics of wireless sensor network are low power, low cost and low complexity. With these functions, wireless sensor network have great potential to develop indoor position system. However, radio signal propagation is easily affected by obstacles that cause diffraction, reflections, scattering and multi-path in the building, the received signal strength needs good calibration method to improve the accuracy of position estimation system. In this thesis we describe grey prediction based location method in wireless sensor network and employ wireless LAN medium (Zigbee/802.15.4). The grey prediction is used to predict the tendency of RSSI (received signal strength indicator), and we also designed dynamic triangular (DTN) location method. We have done some experiments and compare with other classical location methods. The mean distant error of RSSI on mobile user can be within 2.3m at off line stage. As a result, grey predication with DTN provides more accurate predicted position and carries out mean distance error within 1.5 m at run-time stage. At last we implement the indoor navigation system, the main objective of this system is to help mobile user know his location in indoor environment. We integrate the grey prediction and DTN location algorithm in this system and add the map-matching algorithm to improve the accuracy of this system.