This paper addresses the problem of monocular Simultaneous Localization And Mapping on Lie groups using fiducial patterns. For that purpose, we propose a reformulation classical camera model as matrix groups. Thus, define an original-state vector containing pose and set transformations from world frame to each pattern, which constitutes map’s state. Each element state, well pose, are intrinsica...

This paper introduces an extended Kalman filter (EKF) based algorithm for the estimation of closely-spaced path delays and complex coefficients in WCDMA environments. The EKF might be applied either at sample or at symbol level. The model parameters and the sensitivity to the initialization conditions are described for a practical downlink WCDMA scenario, employing root raised cosine pulse shap...

State estimation is the common problem in every area of engineering. There are different filters used to overcome the problem of state estimation like Kalman filter, Particle filters etc. Kalman Filter is popular when the system is linear but when the system is highly non-linear then the different derivatives of Kalman Filter are used like Extended Kalman Filter (EKF), Unscented Kalman filter. ...

Based on presentation of the principles of the EKF and UKF for state estimation, we discuss the differences of the two approaches. Four rather different simulation cases are considered to compare the performance. A simple procedure to include state constraints in the UKF is proposed and tested. The overall impression is that the performance of the UKF is better than the EKF in terms of robustne...

This paper proposes a novel invariant extended Kalman filter (IEKF), recently modified version of the (EKF), to estimate partial discharge (PD) location in transformer insulation system model. An acoustic signal measurement is utilized localize PD location. Unlike conventional EKF methods, where correction term used update state linearly proportional output error, proposed algorithm independent...

This article provides an introduction to Simultaneous Localization And Mapping (SLAM), with the focus on probabilistic SLAM utilizing a feature-based description of the environment. A probabilistic formulation of the SLAM problem is introduced, and a solution based on the Extended Kalman Filter (EKF-SLAM) is shown. Important issues of convergence, consistency, observability, data association an...

This paper presents and proposes a new approach to achieve robust speed estimation in induction motor sensorless control. The estimation method is based on a reduced-order Extended Kalman Filter (EKF), instead of a fullorder EKF. The EKF algorithm uses a reduced-order statespace model structure that is discretized in a particular and innovative way proposed in this paper. With this model struct...

The use of the extended Kalman filter (EKF) is heavily eneenched in non-linear signal procesging applications. However linearisatioa erron inhenmt in the s p e c i f i i n of an EKF can severely degrade its performance. This paper presents a new approach to the robus-tification of the EKF by application of the robust linear design methods b d o n t h e € L wr"inimisationcritexion. Theresults of...