This paper describes a new approach for generalizing the Kalman filter to nonlinear systems. A set of samples are used to parameterize the mean and covariance of a (not necessarily Gaussian) probability distribution. The method yields a filter that is more accurate than an extended Kalman filter (EKF) and easier to implement than an EKF or a Gauss second-order filter. Its effectiveness is demon...

This paper addresses the problem of implementing simultaneous localisation and map building (SLAM) in very large outdoor environments. A method is presented to reduce the computational requirement from ~O(N) to ~O(N), being N the states used to represent all the landmarks and vehicle pose. With this implementation the memory requirement are also reduced to ~O(N). This algorithm presents an effi...

Sensor localization is a central problem for sensor networks. If the sensor positions are uncertain, the target tracking ability of the sensor network is reduced. Sensor localization in underwater environments is traditionally addressed using acoustic range measurements involving known anchor or surface nodes. We explore the usage of triaxial magnetometers and a friendly vessel with known magne...

The development of Kalman filters designed for state estimation of the position and velocity of a spacecraft is attempted and their performance evaluated. Three Kalman Filters are developed, each with its unique characteristics: the Extended Kalman Filter (EKF), the Robust Extended Kalman Filter (REKF) and the Adaptive Robust Extended Kalman Filter (AREKF). The three filters are implemented ass...

We study distributed filtering for a class of uncertain systems over corrupted communication channels. propose robust Kalman filter with stochastic gains, through which upper bounds the conditional mean square estimation errors are calculated online. present collective observability condition, under error is proved to be uniformly bounded if network strongly connected. For better performance, w...

Control of a class of uncertain nonlinear systems, which estimates unavailable state variables, is considered. A new approach for robust tracking control problem of satellite for large rotational maneuvers is presented in this paper. The features of this approach include a strong algorithm to estimate attitude, based on discrete extended Kalman filter combined with a continuous extended Kalman ...

this paper presents a methodology for design of instrumentation sensor networks in non-linear chemical plants. the method utilizes a robust extended kalman filter approach to provide an efficient dynamic data reconciliation. a weighted objective function has been introduced to enable the designer to incorporate each individual process variable with its own operational importance. to enhance the...

A fuzzy Kalman filter algorithm is developed for target tracking applications and its performance evaluated using several numerical examples. The approach is relatively novel. A comparison with Kalman filter and an adaptive tuning algorithm is carried out. The applicability and usefulness of fuzzy logic in data fusion is also demonstrated. The performance of both the extended Kalman filter and ...