轨道机动过程中推力加速度的在线最小方差估计

定位和跟踪空间机动目标时，对目标运动建模受发动机推力的不确定性影响，通过统计处理离散的雷达观测数据实时估计发动机的推力，进而定位和跟踪机动目标便是本文所要研究和解决的问题，本文在地心惯性系建立了常推力轨道机动过程中连续变质量运动模型和离散雷达量测模型，机动过程中质量秒耗量和排气速度作为表征轨控发动机推力的两个近似常量，应用扩展卡尔曼滤波对离散雷达测量数据进行序贯统计处理得到发动机推力的最小方差估计；文中详细地给出了线性化量测模型的变分方程和观测矩阵；仿真结果表明该算法能快速、准确地在线估计轨控发动机的等效推力。

ON-LINE MINIMUM VARIANCE TRACKING FILTER FOR THRUST ACCELERATION ESTIMATION

The uncertainty of thrust acceleration will cause enormous error to model and track the accelerated motion of maneuvered target during orbit transfer process, an on-line minimum variance tracking filter for thrust acceleration estimation is developed in this paper. The propellant mass-flow rate and exhaust velocity are selected as state variants, which are estimated by employing an integral state model and Expended Kalman Filter. The variation equations for measurement vector to state variants have been established to linearize the discrete-time measurement equations. The algorithm has applied successfully to maneuver process in commanding satellite into geo-stationary orbit. The results show the algorithm developed here can estimate thrust acceleration precisely and quickly during orbit transfer process.