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低轨遥感卫星星载GPS精密快速定轨算法 被引量:3

GPS Based Orbit Determination Algorithm with High Precision and Low Computational Complexity for LEO Remote Sensing Satellites
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摘要 对低轨遥感卫星的精密定轨在理论上和实践上均有较高的技术难度,传统的定轨算法难以兼顾定轨精度和低运算复杂度的要求。为此,将交互式多模型算法(IMM)和多速率跟踪(MRT)技术引入卫星精密定轨技术研究,提出一种新定轨滤波算法。以IMM算法为框架,通过建立多模型集,降低对复杂动力学模型的建模误差,并根据各模型的线性化程度,综合选配粒子滤波算法和卡尔曼滤波算法,提高了滤波精度;同时,根据MRT思想,将原始观测信息压缩映射至模式空间,在模式空间实现低速率滤波,以降低算法的运算量。试验结果表明,算法较传统的卡尔曼滤波算法三轴定轨精度提高约47%,而运算速率较粒子滤波算法降低约40%;可见该算法在具有较低运算复杂度的基础上,具有较高的定轨精度,能够满足后续高分辨率遥感卫星对卫星定轨的要求。 High precision orbit determination of LEO remote sensing satellites is difficult both in theory and practice .The traditional method can not meet the requirements of the orbit determination accuracy and low computational complexity . So , the interactive multi-model algorithm (IMM ) and multi-rate tracking (MRT ) method were introduced into the orbit determination .And a novel orbit determination algorithm was proposed based on IMM and MRT . Low kinematics model error was achieved by IMM algorithm . According to the linearization degree of the models , Kalman filter or particle filter was choose respectively to improve the filtering accuracy .Meanwhile ,original observation data was compressed in pattern space to reduce the computational complexity . The proposed algorithm is better than the traditional Kalman filter algorithm , and can improve the accuracy of about 47% . While the computational complexity reduces about 40% compared with particle filter algorithm . The results show that the proposed method can efficiently improve the orbit determination precision with low computational complexity compared with traditional algorithm . It can meet the requirements on orbit determination for the remote sensing satellites .
出处 《中国空间科学技术》 EI CSCD 北大核心 2014年第2期54-61,共8页 Chinese Space Science and Technology
关键词 定轨滤波 多速率模型 交互式多模型 遥感卫星 低地球轨道 Orbit determination Multi-rate tracking method Interactive multi-model Remote sensing LEO
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参考文献8

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