In 1960 Rudolph E. Kalman published his now famous article describing a recursive solution to the discrete-data linear filtering problem (Kalman, “A new approach to linear filtering and prediction problems,” Transactions of the ASME—Journal of Basic Engineering, 82 (D), 35–45, 1960). Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of e...

The accuracy of Global Positioning System (GPS) is increased with the coupling to Inertial Navigation System (INS) to accomplish navigation. This paper proposes an algorithm to filter and fuse the GPS and INS information. Sigma point kalman filter is employed to simulate the information convergence of the dynamic model which maintains better performance in nonlinear system. So we can obtain a b...

An accurate Linear Regression Kalman Filter (LRKF) for nonlinear systems called Smart Sampling Kalman Filter (S2KF) is introduced. It is based on a new low-discrepancy Dirac Mixture approximation of Gaussian densities. The approximation comprises an arbitrary number of optimally and deterministically placed samples in the entire state space, so that the filter resolution can be adapted to eithe...

This work develops an algorithm to initialize an Unscented Kalman Filter using a Particle Filter for applications with initial non-Gaussian probability density functions. The method is applied to estimating the position of a road vehicle along a one-mile test track using terrain-based localization where the pitch response of the vehicle is compared to a premeasured pitch map of the test track. ...

Recursive Bayesian Estimation (RBE) is a widespread solution for visual tracking as well as for applications in other domains where a hidden state is estimated recursively from noisy measurements. From a practical point of view, deployment of RBE filters is limited by the assumption of complete knowledge on the process and measurement statistics. These missing tokens of information lead to an a...

A new kind of particle filter is proposed for the state estimation of nonlinear system. The proposed algorithm based on Quadrature Kalman Filter by using integral pruning factor, which optimizes and reorganizes the integration point. New algorithm overcomes the particle degeneration phenomenon well by using Pruning Quadrature Kalman Filter to produce optimized proposal distribution function. In...

Recently, the range of available radio frequency identification (RFID) tags has been widened to include smart RFID tags which can monitor their varying surroundings. One of the most important factors for better performance of smart RFID system is accurate measurement from various sensors. In the multi-sensing environment, some noisy signals are obtained because of the changing surroundings. We ...

As a result of the lack of the knowledge with regard to the statistical properties of the dynamic models and operational observations, as well as the computational burden related to the high dimensionality of the realistic data assimilation problems especially those complex nonlinear filtering problems, the ensemble Kalman filter scheme has been paid much more attention in recent years and has ...