the error of inertial navigation systems increase versus time, therefore for achieving higher accuracy specially in long time navigations we have to use an aiding system. global positioning system is the best aiding system in this case. in this paper we first simulate a gps and ins; then simulate tightly integration and finally review adaptation method of kalman filtering a fuzzy adaptive kalma...

A new approach for single channel speech enhancement based on Kalman filtering and masking properties of the human auditory system is proposed in the paper. A standard time-varying Kalman filtering method is extended by combining the calculation of noise masking thresholds during the process of parameter updating. Simulation results of a traditional spectral subtraction method, an extended spec...

The problem of estimating unobserved latent variables from observed market data arises frequently in mathematical finance. Kalman filter, first proposed in Kalman (1960), and its generalizations have been the main tools for estimating the unobserved variables from the observed ones in econometrics and in engineering for several decades and their use is now becoming common in finance. Kalman fil...

This paper considers the Linear Minimum Variance recursive state estimation for the linear discrete time dynamic system with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is shown that such system can be converted to a linear dynamic system with deterministic parameter matrices but state-dependent process and measurement noises. It is pro...

In this paper, we consider the problem of 24-hour ahead short-term load forecasting; the formulation is based on the nonlinear Kalman filtering. Our formulation takes into account weather conditions as well as previous trends. Effects of weather as well as prior consumptions are nonlinear functions; hence our choice. We compare our proposed method with the standard Kalman filtering approach and...

Localization is one of the fundamental problems in mobile robot navigation. Past experiments show that in general grid-based Markov localization is more robust than Kalman filtering while the latter can be more accurate than the former. Recently new methods for localization employing particle filters became popular. In this paper we compare different localization methods using Kalman filtering,...

This paper develops an analytical method of truncating inequality constrained Gaussian distributed variables where the constraints are themselves described by Gaussian distributions. Existing truncation methods either assume hard constraints, or use numerical methods to handle uncertain constraints. The proposed approach introduces moment-based Gaussian approximations of the truncated distribut...