This paper proposes a new distributed Kalman filtering fusion with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is proved that under a mild condition the fused state estimate is equivalent to the centralized Kalman filtering using all sensor measurements; therefore, it achieves the best performance. More importantly, this result can be a...

This paper investigates the performance of the Kalman filter as a timing recovery system in tracking mode, subject to a wide range of operating conditions. Our simulation compares the Kalman filter and the phase-locked loop based on the number of divergences for various values of timing disturbance and SNR. They are shown to work equally well in low SNR and disturbance. However, the Kalman filt...

The practical aspects of efficient implementation of the Kalman Filter Bank for scenario analysis are considered. Such implementation have to shorten running time, computational cost, and memory demands, required for computer model of the Kalman Filter Bank. The first requirement is met by concurrent computing. The second and third requirements are satisfied by substitution the Equivalent Kalma...

A 4-dimensional ensemble Kalman filter method (4DEnKF), which adapts ensemble Kalman filtering to the assimilation of observations that are asynchronous with the analysis cycle, is discussed. In the ideal case of linear dynamics between consecutive analyses, the algorithm is equivalent to Kalman filtering assimilation at each observation time. Tests of 4DEnKF on the Lorenz 40 variable model are...

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...

Detection and tracking is the most important technique in the synthetic environment. In this paper we are proposed the real time detection and tracking algorithm using Kalman filter. Kalman filter is based on the assumption base, it is the predictable algorithm through which we can detect and track the human poses. In this paper we design an algorithm to the track of human poses with the help o...

This paper deals with the problem of speech enhancement when a corrupted speech signal with an additive Gaussian white noise is the only information available for processing. Speech enhancement aims to improve speech quality by using various algorithms. The objective of enhancement is improvement in intelligibility and/or overall perceptual quality of degraded speech signal using audio signal p...

The Kalman filter combines forecasts and new observations to obtain an estimation which is optimal in the sense of a minimum average quadratic error. The Kalman filter has two main restrictions: (i) the dynamical system is assumed linear and (ii) forecasting errors and observational noises are projected onto Gaussian distributions. Here, we offer an important generalization to the case where er...

A solution to the state estimation problem of systems with unmeasurable non-zero mean inputs/disturbances, which do not satisfy the disturbance decoupling conditions, is given using the Kalman filtering and Bayesian estimation theory. The proposed estimation algorithm, named Supervisory Kalman Filter (SKF), consists of a Kalman filter with an extra update step which is inspired by the particle ...