低空无人机航空摄影高度自动测量方法研究

为控制低空无人机摄影高度,获得更加清晰的地理信息图像,需要对低空无人机摄影高度自动测量方法进行优化研究;当前方法主要利用射影几何知识的自动化标定方法实现低空无人机航空摄影高度的自动测量;该方法存在噪声影响严重,且测量误差较大的问题;为此,提出一种基于多传感器与卡尔曼滤波相结合的低空无人机航空摄影高度自动测量方法;该方法首先通过分析气压测量法计算各种气压因素对低空无人机航空摄影高度的影响,然后推导出大气对流层内气压随低空无人机航空摄影高度的变化；然后采用双GPS系统同时工作,对GPS、气压高度计和IMU测量获得的低空无人机航空摄影高度信号进行冗余备份；采用基于二阶多项式的修正方法对低空无人机航空摄影传感器输出值进行补偿和修正；根据动力学方程建立低空无人机航空摄影的动力学方程获得高度测量状态方程；最后采用卡尔曼滤波的线性最小方差估计准则对低空无人机航空摄影高度进行均方差估计计算,实现低空高度自动测量与校正。实验结果表明,所提方法具有精度高、收敛性好且滤波效果理想的优势。

Research on Automatic Measurement Method of Aerial Photogrammetry in Low Altitude UAV

In order to control the altitude of low altitude unmanned aerial vehicle (UAV) and obtain clearer geographical information images, it is necessary to optimize the height measurement method of low altitude unmanned aerial vehicle (UAV). The current method mainly uses the automatic calibration method of projective geometry knowledge to realize automatic aerial photogrammetry height measurement of low altitude unmanned aerial vehicle (UAV). The method has the problems of serious noise influence and large measurement error. Therefore, a highly automatic aerial photogrammetry method for low altitude unmanned aerial vehicle (UAV) based on multisensor and Calman filtering is proposed. Firstly, through the analysis of aerial photography has no effect on the height of the low pressure air pressure measurement method for calculation of various factors, and then push the troposphere with low pressure induced no change in aerial photography height; and then the double GPS system work at the same time, for the low altitude GPS, altimeter and IMU measurements obtained the UAV aerial photography altitude signal redundant backup; using two order polynomial correction method based on low altitude UAV aerial photography sensor output value compensation and correction; according to the kinetic equations of dynamics equation of low altitude UAV aerial photography obtained by measuring the height of the state equation; linear minimum variance estimation criterion Calman filtering of low altitude UAV aerial photography were highly variance estimation and realization of low altitude automatic measurement and calibration. Experimental results show that the proposed method has the advantages of high precision, good convergence and ideal filtering effect.