Paper Info
Title
A Bayesian Approach To Predicting An Unknown Number Of Targets Based On Sensor Performance
Abstract
Estimating remaining targets after some attempt has been made to detect an overall, unknown number of targets is critical to determining the potential threat associated with these remaining targets. This paper presents a Bayesian approach to calculate the distribution on the number of remaining targets given the sensor performance and the number of targets detected. For a single sensor, a closed form posterior distribution on remaining targets is derived. For multiple sensors, the corresponding posterior distribution is developed. A naive implementation of this calculation is shown to be computationally prohibitive, and an efficient means for performing the calculation is presented.
Year
DOI
Venue
2006
10.1109/ICIF.2006.301776
2006 9TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4
Keywords
Field
DocType
sensor management, Dirichlet-Multinomial, hierarchical model
Pattern recognition,Computer science,Posterior probability,Sensor fusion,Probability distribution,Artificial intelligence,Sampling (statistics),Estimation theory,Multiple sensors,Bayes' theorem,Bayesian probability
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Karna Bryan11076.94
Craig Carthel215025.31