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- 2018
RTK/INS紧组合算法在卫星数不足情况下的性能分析
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Abstract:
设计了一套基于集中式卡尔曼滤波的实时动态定位（real-time kinematic，RTK）/惯性导航系统（inertial navigation system，INS）紧组合算法，通过实测车载数据对比分析了3颗可用卫星时的固定解和浮点解在位置漂移误差水平和模糊度恢复时间上的差异，验证了该算法在卫星较少情况下的良好性能。该算法在即使观测卫星不足4颗时使用固定解或浮点解进行滤波更新，提高了组合导航在复杂环境下的位置精度，并加快了模糊度恢复过程。实验结果表明，使用中等精度的惯导，在可见卫星数为3颗时，失锁30 s时的水平位置漂移误差为0.3 m；失锁60 s内，平均1~2 s就能可靠地恢复整周模糊度。在位置漂移误差与模糊度恢复方面，固定解和浮点解在GNSS信号短期部分失锁时的差异并不显著，但同时都明显优于信号完全失锁情形
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