Sensor Fusion in Smartphones : with Application to Car Racing Performance Analysis

Abstract: Today's smartphones are equipped with a variety of different sensors such as GPS receivers, accelerometers, gyroscopes and magnetometers, making smartphones viable tools in many applications. The computational capacity of smartphones allows for software applications running advanced signal processing algorithms. Thus, attaching a smartphone inside a car makes it possible to estimate kinematics of the vehicle by fusing information from the different sensors inside the smartphone. Fusing information from different sources for improving estimation quality is a well-known problem and there exist a lot of methods and algorithms in this area. This thesis approaches the sensor fusion problem of estimating kinematics of cars using smartphones for the purpose of analysing driving performance. Different varieties of the coordinated turn model for describing the vehicle dynamics are investigated. Also, different measurement models are evaluated where bias errors of the sensors are taken into consideration. Pre-filtering and construction of pseudo-measurements are also considered which allow for use of state space models with a lower dimension.