ST_CPF.pdf (1.52 MB)
Coordinated standoff tracking of in- and out-of-surveillance targets using constrained particle filter for UAVs
conference contribution
posted on 2015-08-10, 13:18 authored by Hd Oh, Cunjia LiuCunjia Liu, Seungkeun Kim, Hyo-Sang Shin, Wen-Hua ChenWen-Hua ChenThis paper presents a new standoff tracking
framework of a moving ground target using UAVs with a limited
sensing capability such as sensor field-of-view and motion
constraints. To maintain persistent track of the target even in
case of target loss (out of surveillance) for a certain period, this
study predicts the target existence area using the particle filter,
and produces control commands to ensure that all predicted
particles can be covered by the field-of-view of the UAV sensor
at all times. To improve target prediction/estimation accuracy,
the road information is incorporated into the constrained
particle filter where the road boundaries are modelled as
nonlinear inequality constraints. Both Lyapunov vector field
guidance and nonlinear model predictive control methods are
applied for the standoff tracking and phase angle control, and
the advantages and disadvantages of them are compared using
numerical simulation results.
History
School
- Aeronautical, Automotive, Chemical and Materials Engineering
Department
- Aeronautical and Automotive Engineering
Published in
IEEE Intelligent Vehicles SymposiumCitation
OH, H. ... et al, 2015. Coordinated standoff tracking of in- and out-of-surveillance targets using constrained particle filter for UAVs. IN: Proceedings of the IEEE Intelligent Vehicles Symposium, 28th June - 1st July 2015, Seoul, South Korea, pp.499-504.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publication date
2015Notes
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISBN
9781467372671Publisher version
Language
- en