A multiframe assignment algorithm for single sensor bearings-only tracking
Date
2010
Authors
Sathyan, Thuraiappah
Sinha, A.
Mallick, M.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Proceedings of the 13th International Conference on Information Fusion (Fusion 2010): pp.1-8
Statement of Responsibility
T. Sathyan, A. Sinha, M. Mallick
Conference Name
International Conference on Information Fusion (13th : 2010 : Edinburgh, United Kingdom)
FUSION '10
FUSION '10
Abstract
Bearings-only tracking (BOT) using a single maneuvering platform has been studied extensively in the past. However, only a few studies exist in the open literature that deal with measurement origin uncertainty. Most publications are concerned with finding the best filtering approach, since BOT is inherently nonlinear, or finding the optimal maneuver strategy for the sensor platform to improve observability. We consider measurement origin uncertainty due to the existence of multiple targets in the surveillance region, non-unity detection probability, and false alarms. Our algorithm uses the multiframe assignment (MFA) to solve the data association problem, and filtering is performed using the unscented Kalman filter (UKF). We employ both the modified and log polar coordinate systems. Simulation results show that the proposed algorithm is very effective in terms of tracking accuracy and track maintenance capability, especially when formulated in the log polar coordinate system.
School/Discipline
School of Computer Science
Dissertation Note
Provenance
Description
Access Status
Rights
Copyright status unknown