A hybrid adaptive approach to improve position tracking measurements

Abstract

Position tracking of a user or an object has caught many researchers and entrepreneurs’ attention. It has a significant market opportunity as well as applications in daily life such as Earth sciences, intelligent transportation systems, machine control, mapping, surveying, surveillance, tracking, and vehicle testing. The accuracy of different positioning methods depends upon the accuracy of underlying technology and environmental conditions. In this paper, a hybrid adaptive method is developed to enhance the accuracy of positioning. Based on the accuracy and the environments, a coefficient (weight) vector is assigned to the coordinates obtained from INS, GPS, Cellular Network, and Wi-Fi methods. Subsequently, the weighted average method is used to integrate the coordinates to compute the location. The proposed method is tested in an experimental study with different distance settings. The accuracy and robustness of suggested method are validated with GPS and INS hybrids.

Keywords

• GPS
• Indoor positioning
• INS positioning
• Localization
• Mobile positioning
• Wi-Fi positioning