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This paper describes the development and hardware-in-the-loop testing of an Extended Kalman Filter (EKF) for attitude estimation. After literature review, a multi-mode solution to the estimation problem is introduced. It uses the sensor measurements optimally relying on the magnetic and acceleration data on the ground, and magnetic and GPS data in the air. An emergency aerial mode dealing with lost...
This paper presents the problem of sensor fusion to estimate a walking person position. Simple walking person moving model is introduced. We propose two filtering algorithms to solve the present problem. The first algorithm represents an extended Kalman filter (EKF) model which is based on the principle of the state transition matrix and observation matrix linearization under Taylor series expansions...
This paper presents a new form of Kalman filter-the sigmaRho filter-useful for operational implementation in applications where stability and throughput requirements stress traditional implementations. The new mechanization has the benefits of square root filters in both promoting stability and reducing dynamic range of propagated terms. State standard deviations and correlation coefficients are propagated...
A flux linkage estimation method for induction motor based on extended Kalman filter theory (EKF) is presented in this paper. In order to improve the accuracy of filtering, genetic algorithm (GA) is introduced to optimize the noise matrix, and also filtering parameters in EKF. Simulation results show that the flux observer with optimized filtering parameter has better estimation accuracy and dynamic...
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