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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.
Aiming at the problem of unstable and easily disturbed altitude measurement information of small unmanned rotorcraft during autonomous flight, an adaptive altitude information fusion method based on filtered data is proposed to improve the accuracy and reliability of altitude measurement information of unmanned rotorcraft. Based on the wavelet decomposition and reconstruction method, wavelet decomposition and reconstruction method is used to eliminate the high frequency noise in the original measurement data. According to the phenomenon that the measurement accuracy of the GPS is affected by the number of satellites found, the adaptive Kalman filtering method is proposed to realize the altitude information The feasibility and effectiveness of this method are verified by autonomous hovering and three-dimensional flight tracking flight tests.