Key points are not available for this paper at this time.
This paper demonstrates a method for estimating key vehicle states and sensor biases using Global Positioning System (GPS) and an Internal Navigation System (INS). Two Kalman filters, a model based filter and a kinematic filter, are used to integrate the INS sensors with GPS heading and velocity to provide a high update rate of the vehicle states and sensor biases. Additional key vehicle parameters, such as tire-cornering stiffness, are identified and used to correct the model based estimator. The vehicle estimated states compare favorable with values predicted with a theoretical model.
Anderson et al. (Thu,) studied this question.