A labeled random finite set spawning model
MetadataShow full item record
Funding and Sponsorship
© 2017 IEEE. Previous labeled random finite set filter developments use a target motion model that only accounts for survival and birth. While such a model provides the means for a multi-target tracking filter such as the Generalized Labeled Multi-Bernoulli filter to capture target births and deaths in a wide variety of applications, it lacks the capability to capture the lineages of spawned target tracks. In this paper, we propose a labeled random finite set spawning model and derive the resulting multi-target prediction and filtering densities. This formulation enables the joint estimation of spawned object's state and and information regarding its lineage.
Showing items related by title, author, creator and subject.
Bryant, D.; Vo, Ba Tuong; Vo, Ba-Ngu; Jones, B. (2018)Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter, such as the generalized labeled ...
Parsons, Miles James Gerard (2009)Techniques of single- and multi-beam active acoustics and the passive recording of fish vocalisations were employed to evaluate the benefits and limitations of each technique as a method for assessing and monitoring fish ...
Jones, B.; Vo, Ba Tuong; Vo, Ba-Ngu (2016)Space-object tracking systems require robust and accurate methods of multi-target state estimation and prediction. This paper presents the application of labeled multi-Bernoulli filters for space-object tracking, and ...