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摘要: 针对月球车定位，设计和推导了一种基于甚长基线干涉测量（very long baseline interferometry，VLBI）和天文导航系统（celestial navigation system，CNS）相结合的月球车联合定位方法，并采用联邦卡尔曼滤波来实现位置信息的最优估计以增强系统的可靠性和容错能力。最后，通过嫦娥-3号（CE-3）实测数据的解算证明了该方法较使用最小二乘法进行联合解算和单独采用VLBI方法定位，可以获得更高的月球车定位精度。同时，也有效地保障了月球车定位的可靠性和稳定性。Abstract: A co-localization method for lunar rover positioning based on very long baseline interferometry (VLBI) and celestial navigation systems (CNS) is presented in the paper. A federated kalman filter was utilized to implement optimal estimation of position information in order to enhance reliability and fault tolerance ability of the system. Experimentalresults calculated with measurement data from the Chang'E-3(CE-3) mission demonstrate that this method improves the positioning accuracy of the lunar rover comparing with VLBI alone or joint calculation with Least Squares method. Furthermore, this method also guarantees the reliability and stability of lunar rover positioning.
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Keywords:
- VLBI /
- celestial navigation /
- lunar rover /
- co-localization /
- federated kalman filter
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图 2 联合解算和VLBI单独解算的对比
Figure 2. Comparison of Joint Solution and Single Solution of VLBI
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图 3 经纬度方向误差对比
Figure 3. Comparison of Error in Longitude Direction & Latitudinal Direction
表 1 基线残差平均值和闭合值/m
Table 1 The Mean Value and the Closure Value of Baseline Residual/m
残差 UR-KM-TM UR-KM-BJ UR-BJ-TM TM-BJ-KM 单一残差平均值 -2.56 0.31 0.67 -2.61 单一残差闭合差 3.44 0.16 -0.15 -3.42 联合残差平均值 -2.51 0.32 0.66 -2.57 联合残差闭合差 3.40 0.16 -0.14 -3.37 
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