ADAPTIVE KALMAN FILTER FORECASTING FOR ROAD MAINTAINERS

Doppler and bearing tracking using fuzzy adaptive unscented Kalman filter

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...

A New Adaptive Extended Kalman Filter for a Class of Nonlinear Systems

This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

DATA FORECASTING USING KALMAN FILTER ' Alessandro GIROLAMI

This paper shows the "Sequential PrQjection Algorithm" application results, originated by the Bell System [1] and [2], forecasting the yearly representative traffic" values (YRV*) of III different route types of four years data (1983-1986), one step ahead. A seasonal algorithm using monthly data (MRV*) [3], will support the former, however, requiring an exact determination of parameters to succ...

Extended Kalman Filter Based Fuzzy Adaptive Filter

Kalman Filter Algorithm for Adaptive Digital Predistortion

This paper introduces a recursive algorithm of Kalman filter for digital predistorter parameters extraction based on memory polynomials predistorter model. The predistorter model is firstly formulated as linear regression expression. Then we derive the state-space equation of the model and attain the steps of the algorithm. Finally, the accuracy and stability of the algorithm is proved by simul...