Title
Robust Estimation Of A Maneuvering Target From Multiple Unmanned Air Vehicles' Measurements
Keywords
Cooperative; Estimation; H-infinity filter; Kalman filter; Tracking
Abstract
When multiple UAVs collaborate to track a maneuvering target, their position measurement sensors are sometimes corrupted by noise biases (e.g. sensor drifting). In this case, the zero-mean noise assumption of the Kalman filter is therefore violated and the desired optimal estimate will not be guaranteed. In this paper, an H-infinity filter is utilized to estimate the position of the maneuvering target to compensate for non-zero-mean noise. Furthermore, the constrained H-infinity filter is shown to be superior to the Kalman filter. © 2010 IEEE.
Publication Date
7-16-2010
Publication Title
2010 International Symposium on Collaborative Technologies and Systems, CTS 2010
Number of Pages
537-545
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CTS.2010.5478465
Copyright Status
Unknown
Socpus ID
77954470508 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77954470508
STARS Citation
Allen, Randal; Lin, Kuo Chi; and Xu, Chengying, "Robust Estimation Of A Maneuvering Target From Multiple Unmanned Air Vehicles' Measurements" (2010). Scopus Export 2010-2014. 1065.
https://stars.library.ucf.edu/scopus2010/1065