Lesson 16 State Estimation: Prediction
Summary
Prediction, filtering, and smoothing are three types of mean-squared state estimation that have been developed during the past 35 years. The purpose of this lesson is to study prediction.
A predicted estimate of a state vector x(k) uses measurements that occur earlier than tk and a model to make the transition from the last time point, say tj, at which a measurement is available to tk. The success of prediction depends on the quality of the model. In state estimation we use the state equation model. Without a model, prediction is dubious at best.
Filtered and predicted state estimates are very tightly coupled together; hence, most of the results from this lesson cannot be implemented until we have ...
Get Lessons in Estimation Theory for Signal Processing, Communications, and Control, Second Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.