Fuzzy adaptive Kalman filtering for spacecraft celestial navigation
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摘要: 星光折射间接敏感地平的自主天文导航方法能够获得很高的导航精度,但由于大气密度模型时空分辨率不高,这种方法所敏感的地平有可能出现较大的瞬时误差,从而导致导航滤波器精度降低,有时甚至发散.为了解决这一问题,提出将模糊推理系统应用于自主天文导航,研究基于Unscented卡尔曼滤波的模糊自适应算法,使导航滤波器在观测值异常时具有一定的自适应能力.计算机仿真结果验证了该方法的有效性.
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关键词:
- 自主式导航 /
- 自适应滤波 /
- 星光大气折射 /
- Unscented卡尔曼滤波 /
- 模糊推理系统
Abstract: High positioning precision can be obtained by autonomous navigation method based on indirectly sensing horizon by stellar atmospheric refraction. Because of the limited resolution of the atmosphere density model, large instantaneous error would occur in the horizon sensed by this method. In this case, the performance of the navigation filter would be degraded, even divergent. A fuzzy inference system was applied to autonomous celestial navigation and a fuzzy adaptive algorithm based on the Unscented Kalman filter was presented to resolve the problem above. Stronger adaptive ability of navigation filter can be obtained by this adaptive algorithm when the observation is abnormal. The computer simulation results demonstrate the validity of this method. -
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