-For the rapid development high-speed railway system, improvement approach of the velocity measurement accuracy has been studied based on multiple speed sensors on high-speed train. In this method, the velocity measurement data from multi-channel speed sensors were dealt through data fusion of arithmetic mean filter, weighted arithmetic mean filter, Federated Kalman filter and adaptive Federate...

The particle filter (PF) is a novel technique that has sufficiently good estimation results for the nonlinear/non-Gaussian systems. However, PF is inconsistent that caused mainly by loss of particle diversity in resampling step and unknown a priori knowledge of the noise statistics. This paper introduces a new modified particle filter called adaptive unscented particle filter (AUPF) to overcome th...

this paper studies the use of unscented kalman filters (ukf) to estimate nonlinear dynamics and, specifically, adaptive determination of scaling parameters in these filters. due to lack of analytic solution and use of numerical methods instead, the computational load of these filters increases drastically. in this paper, a new method is proposed based on interactive multiple models (imm) which ...

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stoch...

− In this paper a development of an adaptive Kalman filter through a fuzzy inference system (FIS) is outlined. The adaptation is concerned with the imposition of conditions under which the filter measurement noise covariance matrix R or the process noise covariance matrix Q are estimated. The adaptive adjustment is carried out using a FIS based on the whiteness of the filter innovation sequence...

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...

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...

An adaptive extended Kalman filter is developed and investigated for a transient heat transfer problem in which a high heat flux spot source is applied on one side of a thin plate and ultrasonic pulse time of flight is measured between spatially separated transducers on the opposite side of the plate. The novel approach is based on the uncertainty in the state model covariance and leverages tre...

In this paper, we describe a new adaptive system for the enhancement of autoregressive (AR) signals which are disturbed by additive broadband noise. The system is comprised of an adaptive Kalman filter operating as a fixed-lag smoother and a subsystem for AR parameter estimation. As opposed to the conventional approach of employing an extended Kalman filter, we estimate the Kalman filter parame...