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Missing sensor data is a common problem which severely influences the overall performance of today's dataintensive applications. In order to address this important issue, a resilient Extended Kalman Filter is proposed for discrete-time nonlinear stochastic system and measurement equations with sensor failures and random gain perturbations. The failure mechanisms of multiple sensors are assumed to...
For the time-variant multisensor systems with correlated measurement noises and different measurement matrices, on the basis of recursive least squares (RLS) method, least squares(LS) method and Kalman filtering theory, two information fusion Kalman filters are put forward. The theory is that firstly Cholesky factorization is used to convert the former multisensor systems into noise irrelative and...
Based on the Kalman filtering method and white noise estimation theory, under linear minimum variance information fusion criterion weighted by scalars, a multisensor optimal information fusion white noise deconvolution filter is presented for multisensor systems with system deviation,ARMA colored measurement noise and white noise. The formula of computing cross-covariances among filtering errors of...
For the dynamics system of multiple launch rocket s, measuring error of ballistic parameters will appear under the influence of noise disturbance signals. The method of filtrating and estimating the ballistic parameters in the flight of multiple launch rocket is putted forward based on the theory of Kalman filter in this paper. And a filtrating example is also demonstrated in order to get more precise...
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