HyPE: Hybrid particle-element approach for recursive Bayesian searching-and-tracking

Abstract

This paper presents a hybrid particle-element approach, HyPE, suitable for recursive Bayesian searching-and-tracking (SAT). The hybrid concept, to synthesize two recursive Bayesian estimation (RBE) methods to represent and maintain the belief about all states in a dynamic system, is distinct from the concept behind "mixed approaches", such as Rao-Blackwellized particle filtering, which use different RBE methods for different states. HyPE eliminates the need for computationally expensive numerical integration in the prediction stage and allows space reconfiguration, via remeshing, at minimal computational cost. Numerical examples show the efficacy of the hybrid approach, and demonstrate its superior performance in SAT scenarios when compared with both the particle filter and the element-based method.