DocumentCode
1808369
Title
How to count targets given only the number of measurements
Author
Streit, Roy L.
Author_Institution
Metron, Inc., Reston, VA, USA
fYear
2013
fDate
9-12 July 2013
Firstpage
1678
Lastpage
1685
Abstract
The Bayes-optimal distribution of the number of targets is derived, given only the numbers of measurements in a sequence of K consecutive sensor scans. Target states and spatial properties of measurements are completely ignored. A backward recursion for the joint probability generating function of the target-measurement count is derived using a branching process model and independent causal influence assumptions. The counting model can be generalized to spatial branching processes.
Keywords
Bayes methods; statistical distributions; Bayes-optimal distribution; Target states; backward recursion; consecutive sensor scan sequence; independent causal influence assumptions; joint probability generating function; spatial branching process model; spatial properties; target-measurement count; Atmospheric modeling; Clutter; Current measurement; Joints; Pediatrics; Random variables; Time measurement; Bayes estimation; Branching processes; Independent causal influence; Point processes; Probability generating function; Spatial branching processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location
Istanbul
Print_ISBN
978-605-86311-1-3
Type
conf
Filename
6641204
Link To Document