星座分布式自主定轨中信息融合方法比较研究 |
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引用本文: | 杨静,魏若愚. 星座分布式自主定轨中信息融合方法比较研究[J]. 北京航空航天大学学报, 2020, 46(7): 1345-1353. DOI: 10.13700/j.bh.1001-5965.2019.0463 |
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作者姓名: | 杨静 魏若愚 |
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作者单位: | 北京航空航天大学 自动化科学与电气工程学院, 北京 100083 |
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基金项目: | 国家自然科学基金61976013 |
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摘 要: | 为了保证大型导航星座在有限的星载运算能力和通信能力下,具备自主运行能力并提供精准位置参考信息,对基于分层结构的星座分布式自主定轨的信息融合方法展开了研究。以地月卫星联合星座作为研究对象,将简单凸组合法、协方差交叉融合法以及在线性最小方差意义下的矩阵加权法和标量加权法等方法应用于子滤波器估计的融合中,对各种融合方法的性能进行了对比分析。仿真结果显示,在采用方差放大技术去相关设计星座分布式自主定轨算法基础上,采用简单凸组合法、矩阵加权法和标量加权法3种融合方法的定轨精度较高,与集中式滤波精度相当,其中标量加权法的计算代价最低;而协方差交叉融合法由于难以准确确定最优系数,其精度低于其他3种方法。
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关 键 词: | 多源信息融合 协方差交叉融合 线性最优加权融合准则 卫星自主定轨 半分布式滤波 |
收稿时间: | 2019-08-30 |
Comparative study on information fusion methods in constellation distributed autonomous orbit determination |
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Affiliation: | School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China |
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Abstract: | In order to ensure that the large-scale navigation constellation has autonomous operation capability and accurate position reference information with limited on-board computing capability and communication capability, the information fusion method of constellation distributed autonomous orbit determination based on hierarchical constellation is studied. Taking the Earth-Moon satellite joint constellation as the research object, covariance convex, covariance intersection and matrix weighting method and scalar weighting method in the sense of linear minimum variance are used to achieve fusion estimation of all sub-filters in distributed filter structure. The performance of various fusion algorithms was compared and analyzed. The simulation results show that, based on the constellation distributed autonomous orbit determination algorithm designed by variance amplifying technique, the orbit determination precision is high when covariance convex and matrix weighting method and scalar weighting method in the sense of linear minimum varianceare used, and the precision is equivalent to the centralized filtering precision, while the precision will get down when covariance intersection fusion is adopted because the optimal coefficient cannot be accurately searched. |
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