基于低轨星网的多目标协同跟踪滤波技术

The low orbit and high density satellite constellation attracts increasing attention due to its wide coverage and its capability of tracking ballistic targets throughout their traces. To cope with the problem of multiple ballistic targets cooperative tracking, this paper proposes a multi-target cooperative tracking filter based on Chi-square distribution and unscented Kalman filter (UKF). Under the assumption of a Chi-square distribution, this paper develops an indicator function of data association on the measurement plane to assign measurements. And based on the assignment, the variable filter structure is adopted to update the states of multi-target. Finally, the evaluation index of multi-target state estimation performance is given. The numerical simulations show that the algorithm proposed in this paper can effectively realize data association on measurement plane and estimate the state of multiple maneuvering targets (MTT) accurately with less computational load.