Maneuvering target tracking using retrospective-cost input estimation
Liang Han, Zhang Ren, Dennis S. Bernstein · IEEE Transactions on Aerospace and Electronic Systems · 2016
This paper uses a Kalman filter with retrospective cost-based input estimation (KF/RCIE) to track maneuvering targets with unknown acceleration. Unlike conventional tracking methods that model the acceleration as a random process, KF/RCIE views the unknown acceleration as a deterministic unknown signal. Retrospective cost optimization is then used to estimate the unknown acceleration. Numerical examples and laboratory experiments illustrate the effectiveness of this approach with comparison to conventional tracking methods.