Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two prob- lems into one interrelated problem, and consider them sim...Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two prob- lems into one interrelated problem, and consider them simultaneously under a sce- nario where space objects only perform a single in-track orbital maneuver during the time intervals between observations. We mathematically formulate this integrated sce- nario as a maximum a posteriori （MAP） estimation. In this work, we propose a novel approach to solve the MAP estimation. More precisely, the corresponding posterior probability of an orbital maneuver and a joint association event can be approximated by the Joint Probabilistic Data Association （JPDA） algorithm. Subsequently, the ma- neuvering parameters are estimated by optimally solving the constrained non-linear least squares iterative process based on the second-order cone programming （SOCP） algorithm. The desired solution is derived according to the MAP criterions. The per- formance and advantages of the proposed approach have been shown by both theoret- ical analysis and simulation results. We hope that our work will stimulate future work on space surveillance and maintenance of a space object catalog.展开更多
文摘Object correlation and maneuver detection are persistent problems in space surveillance and maintenance of a space object catalog. We integrate these two prob- lems into one interrelated problem, and consider them simultaneously under a sce- nario where space objects only perform a single in-track orbital maneuver during the time intervals between observations. We mathematically formulate this integrated sce- nario as a maximum a posteriori （MAP） estimation. In this work, we propose a novel approach to solve the MAP estimation. More precisely, the corresponding posterior probability of an orbital maneuver and a joint association event can be approximated by the Joint Probabilistic Data Association （JPDA） algorithm. Subsequently, the ma- neuvering parameters are estimated by optimally solving the constrained non-linear least squares iterative process based on the second-order cone programming （SOCP） algorithm. The desired solution is derived according to the MAP criterions. The per- formance and advantages of the proposed approach have been shown by both theoret- ical analysis and simulation results. We hope that our work will stimulate future work on space surveillance and maintenance of a space object catalog.
