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机构地区:[1]国防科技大学电子科学与工程学院,湖南长沙410073
出 处:《信号处理》2009年第9期1393-1398,共6页Journal of Signal Processing
基 金:武器装备预研基金资助项目(9140A20010107KG0163)
摘 要:在星对星无源定轨跟踪中,由于卫星运动方程的非线性和隐函数特性,如何建立适合递推滤波的状态预测方程和状态转移矩阵是个首要的问题。根据目标星与观测星相对速度很大的特点,在角度观测之外引入频率观测,然后根据卫星运动的动力学和几何学条件,推导准确的状态预测方程及其对应的状态转移矩阵,并给出了相应的计算方法。结合EKF滤波算法,提出了一种新的基于准确状态预测模型的单星对星测角和测频无源定轨跟踪方法。仿真实例表明,该方法定位性能较仅测角定位法有很大程度改善;且与已有的基于近似状态预测模型的利用角度和频率信息的定轨方法相比,本文方法亦具有更高的估计精度和更快的收敛速度,且两者计算耗时相当。In satellite-to-satellite passive orbit determination and tracking, the motion equation of satellite is nonlinear and it is an implicit function of system state. To find a state prediction formulation which is adapted to recursive filtering, and to derive the corresponding state-transition matrix,is prime and very important. In addition to bearings, Frequency is utilized as another observed quantity, since the velocity of target satellite relatively to observer satellite is great. Based on the kinetics and geometry of satellite motion, an accurate state prediction formulation and the corresponding state-transition matrix are derived, and the computation methods are presented. Then,according to Extended Kalman Filtering (EKF) algorithm, a novel satellite-to-satellite passive orbit determination and tracking method with bearings and frequency measurements is proposed. Simulations are designed and carried out. The results indicate that, the location performance of this method is superior to the bearing-only location method. And compared with the method using an approximate state prediction formulation, higher accuracy of estimation and faster convergence are obtained using the novel method, and the computational complexity of the later is comparable with the former.
分 类 号:V55[航空宇航科学与技术—人机与环境工程]
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