Reinforced Likelihood Box Particle Filter

This letter is concerned with the development of a general scheme for box particle filtering. It based on likelihood computation, most crucial step estimation strategy. The proposed filter takes advantages from strong aspects various existing filters and adds an interesting reinforced computation method that enhances results. An overview Box Particle Filters discussions assumptions used in literature to performance evaluation approach are presented. Also, comparative study obtained results by performing several scenarios illustration example provided highlight efficiency