Rolling horizon state estimator
A technology of state estimation and rolling time domain, applied in the direction of dynamic tree, time register, dynamic search technology, etc., can solve the problems of limited data volume and high cost
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[0056] System Overview
[0057] Figure 1A and Figure 1BA block diagram of a receding horizon state estimator 100 for estimating the state of a vehicle 101 based on a prediction horizon is shown according to some embodiments. The rolling time-domain state estimator borrows some principles from the model predictive controller (MPC), and while satisfying the constraints on the state estimation accuracy of each time step in the prediction time domain, the iterative finite prediction time-domain optimization based on the cost function is used to A subset of external sensors is selected at each time step, with a cost function describing the total communication cost of obtaining external measurements over the forecast time domain. In this way, the rolling temporal state estimator is able to predict future events when selecting a subset of external sensors for each time step to ensure consistent constraint satisfaction while reducing the communication cost of external measurements....
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