Kalman filter based hybrid estimation algorithms have been used in many applications. However, performance analysis of these algorithms is difficult because many of these algorithms use a set of Kalman filters that are coupled with each other. We present an algorithm to compute the means and cross-covariances of the residuals of the set of coupling (or interacting) Kalman filters. Specifically,...

Comparisons of six heating source localisation measurement models are conducted where temperature or ultrasonic time of flight readings provide the measurement update to the extended Kalman filter for estimating the location of a high heat flux spot source on a flat plate. For a particular measurement model, one of two processes are used: 1) directly using the measurements as the measurement ve...

To improve the positioning accuracy and robustness of indoor positioning technology, a fingerprint positioning method is proposed based on the Kalman filter and the probability weighted Bayes algorithm. Firstly, the optimal estimation of signal strength is calculated using the prediction and correction model of Kalman filter, and then the position is estimated using the posterior probability we...

The aim of this study is to fuse GPS(Global Positioning System)/IMU(Inertial Measurement System) by using Kalman filter. We acquired the 6D pose data and compared the accuracy of 3D world model by using the data with Kalman filter and 3D world model by without filtering. Using proposed Kalman filter method, we obtain the exact pose data. This indicates that reconstructed 3D world model, using t...

This article presents a sensorless five level DTC control based on neural networks using Extended Kalman Filter (EKF) applied to Double Star Induction Machine (DSIM). The application of the DTC control brings a very interesting solution to the problems of robustness and dynamics. However, this control has some drawbacks such as the uncontrolled of the switching frequency and the strong ripple t...

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

abstract comparison of food prices in different periods, indicates fluctuations and continually upward trend. any change in agricultural sector variables, as main food supplier, will affect food price. productivity shocks and production gap are examples of such variables. in this paper ,hodrick prescott and kalman filters are used as generators of productivity shocks and production gap series. ...

This paper corrects an unclear treatment of the conventional Kalman filter implementation as presented by M. H. Verhaegen and P. van Dooren in “Numerical aspects of different Kalman filter implementations,” IEEE Trans. Automat. Contr., vol. AC-31, no. 10, pp. 907-917, 1986. This paper shows that habitual, incorrect implementation of the Kalman filter has been the major cause of its sensitivity ...

In this paper, the channel is estimated by using kalman filter. The channel is time varying modeled as a low-Pass tapped delay line filter that is work as the FIR filter with time varying Coefficients. Here Kalman filter technique is used to estimate the time varying coefficient of the channel.