面向无人机高度融合估计的自适应S滤波方法

Adaptive S filtering method for UAV height fusion estimation

针对无人机采用单一传感器测量飞行高度不准以及易受干扰的问题,提出了基于自适应S滤波高度信息融合方法。首先针对各种测高传感器获取的原始数据中含有噪声问题,设计出一种自适应S滤波器。它先将信号经过广义S变换,然后统计对应时刻各个频率的能量幅值,根据不同频率在时间集合上的幅值能量总和,保留能量和占总能量97%的频率,经过S逆变换,从而有效剔除信号中的噪声。再对滤波后的数据进行集中式卡尔曼滤波,得到无人机的高度信息。仿真实验表明,经过自适应S滤波器去噪后融合的高度均方根误差是小波去噪后融合结果的26.3%,具有较高的精度。

A measurement of the UAV's height obtained by single sensor is usually not accurate and easily disturbed. A method of adaptive S-filter for height information fusion is developed to solve the problem. Firstly, an adaptive S-filter is designed to deal with the noise existed in the original data from the sensor. Secondly, the statistics is made on energy amplitudes of each frequency in the corresponding time, in which the energies whose sums are higher than 97% of the sum of total energy are kept. The noise can be effectively eliminated after S-inverse transform. Thirdly, an entralized Kalman filter is used to smooth the data and the height information of UAV can be obtained. The simulation experiment shows that our method of fusing the denoised height data by adaptive S-filter is more accurate than that obtained by wavelet, whose root-mean-square error is 26.3% lower.