Acknowledged author Robert Grover Brown wrote Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises comprising 400 pages back in 2012. Textbook and etextbook are published under ISBN 0470609699 and 9780470609699. Since then Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises textbook was available to sell back to BooksRun online for the top buyback price of $60.54 or rent at the marketplace.
Advances in computers and personal navigation systems have greatly expanded the applications of Kalman filters. A Kalman filter uses information about noise and system dynamics to reduce uncertainty from noisy measurements. Common applications of Kalman filters include such fast-growing fields as autopilot systems, battery state of charge (SoC) estimation, brain-computer interface, dynamic positioning, inertial guidance systems, radar tracking, and satellite navigation systems.
Brown and Hwang's bestselling textbook introduces the theory and applications of Kalman filters for senior undergraduates and graduate students. This revision updates both the research advances in variations on the Kalman filter algorithm and adds a wide range of new application examples. The book emphasizes the application of computational software tools such as MATLAB. The companion website includes M-files to assist students in applying MATLAB to solving end-of-chapter homework problems.