Space　target　surveillance　plays　an　important　role　in　maintaining　space　advantages.　Trajectory　planning　and　attitude　control　are　the　key　technologies　of　space　target　surveillance.　We　propose　a　nonlinear　model　predictive　control　framework　to　plan　the　trajectory　of　the　surveillance　satellite,　track　the　surveillance　target　and　keep　a　certain　distance.　In　particular,　the　orbit　dynamics　and　environmental　disturbance　of　surveillance　satellite　are　taken　into　account.　A　MatLab　based　real-time　nonlinear　model　predictive　control　toolbox　is　used　to　solve　these　problems.　The　toolbox　uses　an　efficient　numerical　method　to　calculate　the　maneuvering　solution　of　MPC,　which　means　that　it　allows　the　prediction　horizon　length　to　be　greatly　extended　and　save　calculation　time.　The　developed　controller　is　simulated　in　a　simulation　scene,　including　the　interference　of　near　ground　environment.　We　show　that　the　proposed　MPC　method　can　be　successfully　applied　to　the　satellite　orbit　planning　and　attitude　control　and　the　MATMPC　toolbox　can　greatly　speed　up　the　solution　of　MPC　optimization　functions.　©　2021　IEEE