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中文摘要：
针对无重置联邦滤波器整体融合精度非最优以及应用于多源信息非等间隔滤波时的适应性问题，提出了基于子滤波器方差阵修正的多源信息非等间隔联邦滤波算法。在不增加额外计算的情况下，通过修正子滤波器滤波方差阵来改善滤波器的融合精度，且以高空长航无人机为应用对象，设计了适用于高空长航无人机的惯性／天文／景象匹配／地形匹配（INS／cNs／sAR／TER）组合非等间隔联邦滤波实现方案，提出了主／子滤波器的状态更新方法，在保持无重置结构容错性强的同时，解决无重置联邦滤波器在应用于多源信息非等间隔滤波时的适应性问题。仿真结果表明所提出的算法能有效改进滤波器性能。
英文摘要：
For the problem of no-reset federated filter overall sub-optimal fusion accuracy and the adjustment of unequal-interval filter for multi-source information,an unequal-interval federated filter algorithm based on sub-filter modified covariance correction for multi-source information is proposed. In the case of barely raising computer load, the filter＇s fusion accuracy is improved by modifying sub-filter＇s covariance. Meanwhile, the INS/CNS/SAR/TER integrated unequal-interval filter implementation scheme for high altitude long endurance（HALE） UAV is designed. The state updating method of the master and sub-filter is proposed,thus the adaptation problem of unequal-interval federated filter algorithm for multi-source information is solved at the same time can keep the good performance of fault-tolerance with no reset mode. The simulation results show that these algorithms have an obvious improvement of fusion accuracy compared with the traditional scheme.
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