Title
Multi-Sensor Joint Detection and Tracking with the Bernoulli Filter
Abstract
This paper proposes a filter for joint detection and tracking of a single target using measurements from multiple sensors under the presence of detection uncertainty and clutter. To capture the target presence/absence in the surveillance region as well as its kinematic state, we represent the target state as a set that can take on either the empty set or a singleton. The uncertainty in such a set is modeled by a Bernoulli random finite set (RFS), and Bayes optimal estimators for joint detection and tracking are presented. A closed-form solution for the linear-Gaussian model is derived and an analytic implementation is proposed for nonlinear models based on the unscented transform. We apply the technique to tracking targets constrained to move on roads with time difference of arrival/frequency difference of arrival (TDOA/FDOA) measurements.
Year
DOI
Venue
2012
10.1109/TAES.2012.6178069
IEEE Trans. Aerospace and Electronic Systems
Keywords
Field
DocType
Sensors,Target tracking,Clutter,Joints,Uncertainty,Filtering theory
Empty set,Finite set,Clutter,Control theory,Measurement uncertainty,Sensor fusion,Unscented transform,FDOA,Multilateration,Mathematics
Journal
Volume
Issue
ISSN
48
2
0018-9251
Citations 
PageRank 
References 
28
1.32
12
Authors
4
Name
Order
Citations
PageRank
Ba Tuong Vo136220.68
Chong Meng See2553.77
Ning Ma3455.95
Wee Teck Ng421671.76