This paper presents sensor data fusion using Unscented Kalman Filter (UKF) to implement high performance vestibulo-ocular reflex (VOR) based vision tracking system for mobile robots. Information from various sensors is required to be integrated using an efficient sensor fusion algorithm to achieve a continuous and robust vision tracking system. We use data from low cost accelerometer, gyroscope...

Abstract Aiming to improve the position and velocity precision of INS/GNSS system during GNSS outages, a novel that combines unscented Kalman filter (UKF) nonlinear autoregressive neural networks with external inputs (NARX) is proposed. The NARX-based module utilized predict measurement updates UKF outages. A new offline approach for selecting optimal NARX suggested tested. This based ...

In a series of recent studies a new approach for applying the Kalman filter to nonlinear system, referred to as Unscented Kalman filter (UKF), was proposed. In this contribution we apply the UKF to several speech processing problems, in which a model with unknown parameters is given to the measured signals. We show that the nonlinearity arises naturally in these problems. Preliminary simulation...

In this paper three different filtering methods, the Extended Kalman Filter (EKF), the Gauss-Hermite Filter (GHF), and the Unscented Kalman Filter (UKF), are compared for state-only and coupled state and parameter estimation when used with log state variables of a model of the immunologic response to the human immunodeficiency virus (HIV) in individuals. The filters are implemented to estimate ...

Kalman filters provide an important technique for estimating the states of engineering systems. With several variations of nonlinear Kalman filters, there is a lack of guidelines for filter selection with respect to a specific research or engineering application. This creates a need for an in-depth discussion of the intricacies of different nonlinear Kalman filters. Particularly of interest for...

Existing polar transfer alignment (TA) algorithms are designed based on linear Kalman filters (KF) to estimate misalignment angles. In the case of a large misalignment angle, these algorithms cannot be applied in order to achieve accurate TA. In this paper, a TA algorithm based on an unscented Kalman filter (UKF) is proposed to solve the problem of the large misalignment angle in the polar regi...

This paper proposes an optimized algorithm for 3-D Point Based Rigid Registration. This algorithm uses an Unscented Kalman filter (UKF) for estimating the state vector of transformation, which can be interpreted as a nonlinear function of translation and rotation. In the previous work, we showed that the drawback of the UKF algorithm in estimating high range rotations is due to its sensitivity ...

The stability problem is one of the existing problems of unscented Kalman filter (UKF), which due to the nonlinearity and complexity of system. The precision will be decreased or even UKF will be halted when the algorithm can’t ensure the state covariance to be positive semidefinite. Based on decomposition of state covariance, the paper first reviews two modified UKFs which can enhance the stat...

Inequalities in the creative industries are known to be persistent and systemic. The model of production in UK film and television (UKF&TV) is argued to exclude on the basis of gender, race and class. This article considers a social category that has been overlooked in these debates: disability. It argues that workers with impairments are ‘doubly disabled’ – in both the labour markets and labou...

We present a simplified drift-flux model (DFM) describing a multiphase (gas-liquid) flow during drilling. The DFM uses a specific slip law, without flow-regime predictions, which allows for transition between single and two phase flows. With this model, we design an Unscented Kalman Filter (UKF) for estimation of unmeasured states, production parameters and slip parameters using real time measu...