In order to improve estimation accuracy of nonliear system with linear measurement model, simplified gauss hermite filter based on sparse grid gauss hermite quadrature (SGHF) is proposed. Comparing to conventional Gauss-Hermite filter (GHF) based on tensor product gauss quadrature rule, simplified SGHF not only maintains GHF’s advantage of precission controllable, high estimation accuracy, but ...

In this paper, we propose an efficient geo-location system for social safety robot using a single base station, where its location is obtained by direction of arrival (DOA) and time of arrival (TOA) of the radio signal. The proposed system requires two reference signals while the conventional systems generally deploy more than three reference signals. For estimating DOA and TOA information toge...

Recently, the Spherical Motion Models (SMM’s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM’s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their perf...

Nonlinear filtering is certainly very important in estimation since most real-world problems are nonlinear. Recently a considerable progress in the nonlinear filtering theory has been made in the area of the sampling-based methods, including both random (Monte Carlo) and deterministic (quasi-Monte Carlo) sampling, and their combination. This work considers the problem of tracking a maneuvering ...

Joint estimation of unknown model parameters and unobserved state componentsfor stochastic, nonlinear dynamic systems is customarily pursued via the extendedKalman filter (EKF). However, in the presence of severe nonlinearities in the equa-tions governing system evolution, the EKF can become unstable and accuracy ofthe estimates gets poor. To improve the results, in this paper w...

A method is introduced for determination of a vector network analyzer’s calibration residual errors for measurement of the reflection coefficient. The method utilizes unscented Kalman filtering and spline interpolation time domain techniques. All three residual errors are calculated by processing the measured reflection coefficient of a single verification device, such as an air line terminated...

The basic problem in Target tracking is to estimate the trajectory of a object from noise corrupted measurements and hence becoming very important field of research as it has wider applications in defense as well as civilian applications. Kalman filter is generally used for such applications. When the process and measurements are non linear extensions of Kalman filters like Extended Kalman Filt...

In this paper, the new nonlinear filter method Cubature Kalman Filter (CKF) is improved to solve the passive location problem. Firstly, the Empirical Mode Decomposition (EMD) algorithm is used to estimate the new measurement noise covariance in the filter process; And then the new covariance of the noise is brought into the circle; Meanwhile, the location process is improved by the way of squar...