Preliminary Investigation of predicting GPS satellite’s signal strength in indoor environments

Abstract

This study presents a method for predicting the GPS signal strength received by devices at each position inside a target floor in a building. The predicted signal strengths can be used as a rough indoor fingerprint localization system without extra infrastructure. Although it has been widely considered as a fact that the current GPS system is still unable to achieve high-precision indoor localization, we attempted to analyze the characteristics of indoor GPS reception by considerable factors. We employ a neural network based system which mainly uses floor plan including wall’s information and window information as well as shapes and heights of neighboring tall buildings. In addition, we integrate the GPS satellite information including its azimuthal angle and elevation angle to estimate line of sight (LOS) from each satellite to the target environment. We evaluate our framework using data obtained in different buildings from different areas in the city and campus.