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针对救援或维护过程中目标突发机动情况,研究了施援卫星的近程相对导航系统及其优化算法。提出可将被救援目标突发的控制加速度视作不确定的干扰因素,用强跟踪无味卡尔曼滤波(STUKF)算法,提高相对导航系统对突变状态的跟踪能力,满足对救援目标相对状态估计的精度要求。仿真结果表明:STUKF提高了对救援目标相对导航信息的实时跟踪能力,保证了滤波过程的数值稳定性,算法有效。
Aiming at the sudden maneuvering of target during the rescue or maintenance, the short-range relative navigation system of the satellite and its optimization algorithm are studied. It is proposed that the controllable acceleration of the rescue target can be considered as an uncertain disturbing factor. With robust tracking of the Unscented Kalman Filter (STUKF) algorithm, the tracking ability of the relative navigation system to the abrupt state can be improved and the relative state estimation of the rescue target Accuracy requirements. The simulation results show that STUKF improves the real-time tracking ability of the relative navigation information of the rescue target, guarantees the numerical stability of the filtering process and the algorithm is effective.