A Novel Approach to Mapping Wi-Fi and Aiding Inertial Navigation Systems: Exploring Indoor Applications

Abstract

Inertial navigation systems (INSs) provide a robust method for obtaining position, velocity, and attitude (PVA). Unfortunately, these systems suffer from drift in the solution due to noise inherent in the inertial sensors used. By leveraging signals of opportunity, this drift may be bounded, and the INS solution becomes more reliable. In this article, we present a novel approach: using Wi-Fi signals to aid INSs. Unlike existing techniques that require accurate measurements and mapping of the radio-frequency (RF) environment, our approach requires minimal calibration based off of a 360° walk around the area of interest with a clear sky background to allow for positional measurements by a GPS unit. A model based on Wi-Fi signals of opportunity is generated to aide the INS. Applications include aiding personnel or autonomous robots in global navigation satellite systems (GNSS)-denied environments with more accurate positioning information.