Sparse observations make single-point track initialization difficult in some multitarget tracking scenarios, including space-object tracking. A probabilistic admissible region approach combines physics- and scenario-based constraints in unobservable directions to reduce ambiguity in the initial state and allows for a birth model consistent with the derivation assumptions in the cardinalized probability hypothesis density filter. The proposed filter enables tracking of simulated space objects via optical or radar observations and establishes custody of newly observed targets when given sparse observations.
CPHD Filter Birth Modeling Using the Probabilistic Admissible Region
IEEE Transactions on Aerospace and Electronic Systems ; 54 , 3 ; 1456-1469
2018-06-01
1345185 byte
Article (Journal)
Electronic Resource
English
IEEE | 2016
|Probabilistic Admissible Region for Multihypothesis Filter Initialization
Online Contents | 2017
|Adaptive Target Birth Intensity for PHD and CPHD Filters
IEEE | 2012
|