A Generalized Labeled Multi-Bernoulli Filter with Object Spawning

Abstract

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 Multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide variety of applications, it lacks the capability to capture spawned tracks and their lineages. In this paper, we propose a new GLMB based filter that formally incorporates spawning, in addition to birth. This formulation enables the joint estimation of a spawned object's state and information regarding its lineage. Simulations results demonstrate the efficacy of the proposed formulation.

References in corpus (2)

• Generalized Labeled Multi-Bernoulli Approximation of Multi-Object Densities
• A Particle Multi-Target Tracker for Superpositional Measurements using Labeled Random Finite Sets

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• The Smooth Trajectory Estimator for LMB Filters
• Mitigation of Radar Range Deception Jamming Using Random Finite Sets
• Randomized Multiple Model Multiple Hypothesis Tracking