Application of Extended Kalman Filtering for Estimating Immeasurable Vehicle State Variables

Estimating model error covariance matrix parameters in extended Kalman filtering

The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user. In this paper, we study the filter likelihood technique for estimating the parameters of the model error covariance matrix. The approach is based on computing the likeliho...

Extended Kalman Filtering by

GPS/INS Integration for Vehicle Navigation based on INS Error Analysis in Kalman Filtering

The Global Positioning System (GPS) and an Inertial Navigation System (INS) are two basic navigation systems. Due to their complementary characters in many aspects, a GPS/INS integrated navigation system has been a hot research topic in the recent decade. The Micro Electrical Mechanical Sensors (MEMS) successfully solved the problems of price, size and weight with the traditional INS. Therefore...

Synchronization through Extended Kalman Filtering

We study the synchronization problem in discrete-time via an extended Kalman filter (EKF). That is, synchronization is obtained of transmitter and receiver dynamics in case the receiver is given via an extended Kalman filter that is driven by a noisy drive signal from the transmitter. Extensive computer simulations show that the filter is indeed suitable for synchronization of (noisy) chaotic t...

Multiple Model Framework of Extended Kalman Filtering for Predicting Vehicle Location using Latest Global Positioning System

This paper looks into various practical methods of improving existing collision avoidance systems that loose accuracy in non-straight paths. Different frameworks of models are studied to identify their accuracy in predicting a vehicle’s future location in non-straight path. From a simple mathematical approach to more complex frameworks of multiple Kalman Filters are evaluated to obtain more acc...