3 Tobit Kalman Filter with Time-Correlated Multiplicative Sensor Noises under Redundant Channel Transmission
Since the seminal work in [156], the celebrated Kalman filter (KF) has proven to be a state estimation algorithm of central importance in a variety of engineering applications such as flight control, global position systems (GPS), target tracking and so forth. A standard assumption for the conventional KF is that the system model under consideration should be precisely known, and the process/measurement noises should be completely Gaussian. Such an assumption is, however, not always true because of unavoidable appearance of measurement nonlinearities, modeling uncertainties, networked-induced phenomena (e.g. ...
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