The application of the divided derivative filters is described, applied and compared to the most popular tool in estimation , the extended Kalman filter (EKF). In our work the first order divided difference filter and the second order divided difference filter were simulated and applied to integrated navigation system including inertial measurement unit (i) and global positioning system. These ...

This paper investigates the use of statistical linearization to improve iterative non-linear least squares estimators. In particular, we look at improving long range stereo by filtering feature tracks from sequences of stereo pairs. A novel filter called the Iterated Sigma Point Kalman Filter (ISPKF) is developed from first principles; this filter is shown to achieve superior performance in ter...

We investigate the problem of tracking a moving source in shallow ocean in a Bayesian framework, using acoustic field measurements which are more informative than the commonly employed bearings-only or time-delay measurements. The acoustic field measurement model is described and compared with the bearings-only measurement model. A general approach to Bayesian filtering based on the Gaussian ap...

Department of Electrical Engineering, University of Engineering and Technology, Lahore, Pakistan Contact: : [email protected] [email protected] [email protected] ABSTRACT: This paper presents the sensor-less control of a PMSM using extended Kalman Filter and a four switch three phase inverter implemented using FPGA Spartan 3-e. The system was modeled in Matlab/Simulink® and ver...

In this paper a fuzzy logic based intelligent Extended Kalman filter (EKF) is used for the estimation of speed, rotor position ,direct and quadrature axis current of permanent magnet synchronous motor thereby eliminating the problem of design and tuning of process covariance matrix in EKF algorithm. Unlike in the previous approaches the present work uses only the sensed line currents as measure...

This article presents a solution to the problem of fusing measurements acquired from a monocular camera with inertial data to achieve simultaneous localization and mapping (SLAM) tasks. This paper describes the models used to correctly integrate inertial and vision data in an EKF-SLAM based application, and ways to perform the fusion on low cost hardware. Both synthetic and real sequences show ...

This paper introduces an extended Kalman filter (EKF) based algorithm for the estimation of closely-spaced path delays and complex coefficients in WCDMA environments. The EKF might be applied either at sample or at symbol level. The model parameters and the sensitivity to the initialization conditions are described for a practical downlink WCDMA scenario, employing root raised cosine pulse shap...

This paper presents a novel and cost effective method to be used in the optimization of the Gaussian Frequency Shift Keying (GFSK) at the receiver of the Bluetooth communication system. The proposed method enhances the performance of the noncoherent demodulation schemes by improving the Bit Error Rate (BER) and Frame Error Rate (FER) outcomes. Linear, Extended, and Unscented Kalman Filters are ...

In INS/GPS integration, the data fusion algorithm involves properly handling of nonlinear models. Therefore the nonlinear filtering methods have been commonly applied in the INS/GPS integration to estimate the state vector. The most popular and commonly used method is the Extended Kalman Filter (EKF) which approximates the nonlinear state and measurement equations using the first order Taylor s...

This paper presents a nonlinear approach for data reconciliation. The advantages of this approach over the conventional extended Kalman filtering (EKF) are namely, less linearization errors are generated in the process, and secondly the choice of the objective function is flexible. In this work, two probability density functions, namely the Logistic and Lorentz distribution are proposed as the ...