Abstract
The dynamic models with multilevel inputs are adopted in a kind of multiple model estimator for highly maneuvering target tracking. While the target maneuvers with the continuous time-varying accelerations, the estimator increases the levels to improve the percentage of coverage, which induces two problems: the increase of calculation burden and the decrease of the estimation precision due to the competition between the models. A multilevel input-adaptive multiple model (IAMM) algorithm is proposed, in which the inputs are adjusted according to the prior value and the on-line estimated maneuver parameters by introducing a dualistic distribution. The adaptabilities of the inputs can depict the actual maneuver process better compared with the static multilevel inputs. The simulation proves the effectiveness of IAMM algorithm compared with the IMM (Interacting Multiple Model) estimator with models containing multilevel static inputs.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
