Passive Multi-sensor Maneuvering Target Tracking Based on UKF-IMM Algorithm
Panlong Wu, Xingxiu Li · 2009
For effectively improving the accuracy of tracking a maneuvering target by passive sensors, a novel passive multi-sensor maneuvering target tracking algorithm based on unscented Kalman filter-interacting multiple model (UKF-IMM) is proposed. In this algorithm UKF is used by all models. UKF can avoid linearization of the highly nonlinear equations, and achieve accuracy at least to the second order. This algorithm use Markov process to describe switching probability among the models, while weighting means of inputs and outputs of UKF. Simulation results in passive maneuvering target tracking using three infrared sensors show that the proposed algorithm is more stable and effective.