Multi-sensor Single Maneuvering Target Tracking in Clutter using AMMPF

In this article we consider a single maneuvering target Tracking algorithm in the presence of missing measurements and high clutter environments for multi'sensor target tracking problem. The tracking algorithm is based on the Particle filtering method to predict and update target states. Proposed is the AMM-PF(Auxiliary Multiple Model Particle Filter)[2] method for maneuvering target tracking to improve performance in track estimate and maintenance with a high level of uncertainty. The algorithm we propose is compared to the Extended Kalman Filter(EKF). A simulation study is included.