Efficient generalized labeled multi-bernoulli filter for jump Markov system

This paper proposes efficient implementations for a Generalized Labeled Multi-Bernoulli filter for a Jump Markov System. The proposed filter operates via combining both prediction and update steps into a single step, therefore requiring merely a single truncation procedure. The efficiency of the filter is evaluated using simulation examples with comparison to the existing filter with separate prediction and update steps.