Method of small unmanned aerial rotorcraft altitude information fusion based on wavelet filter
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摘要: 针对小型无人旋翼机自主飞行时高度测量信息不稳定、易受干扰的问题,提出采用基于滤波数据的自适应高度信息融合方法来提高无人旋翼机高度测量信息的精度和可信度.通过基于小波提升算法的小波分解重构方法,消除原始测量数据中的高频噪声;根据全球定位系统的测量精度受搜到卫星数目波动影响的现象,提出利用自适应卡尔曼滤波的方法实现高度信息融合.通过自主悬停和三维航迹跟踪飞行试验验证该方法的可行性和有效性.Abstract: Focusing on the low performance of the sensors for the small unmanned aerial rotorcraft, an adaptive Kalman method based on filter data was proposed to improve the accuracy and reliability of the altitude measurement information. Using the wavelet decomposition and reconstruction filter, the high frequency noise of altitude information for the small unmanned aerial rotorcraft was eliminated. Furthermore, since the global positioning system(GPS) measurement accuracy was influenced by GPS satellite-number fluctuation, an adaptive Kalman filter was used to improve altitude measurement performance. At last, hovering flight and three-dimensional track flight test were used to verify the feasibility and effectiveness of the method.
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