Abstract:

Lowearthorbit (LEO) multitarget tracking plays a key role in the information processing of spacebased optical systems. We propose a tracking method based on the multimodel cardinalized probability hypothesis density (CPHD) filtering. We first construct multiple motion models including a constant axial force model and a twobody gravity for describing the movement of LEO targets. We also build a spacebased measurement model. The extended state is established by combining the motion mode with the target state of the LEO target. Both the posterior probability hypothesis density (PHD) of the extended state and the posterior cardinality distribution of targets are propagated by using the CPHD filtering. Then, the target states and the target numbers are jointly estimated. Simulation results show that the proposed multimodel CPHD filtering achieves better estimation accuracy in target number and target states in comparison with the multimodel PHD filtering and the single model CPHD filtering.

Key words: spacebased optical observation;multimodel;CPHD filtering;LEO;multitarget tracking