基于激光点云数据的无人驾驶航空器系统空中走廊构建

Construction of aerial corridor for unmanned aircraft systems in low altitude airspace based on point cloud of laser scanner

摘要:

对低空安全和个人隐私保护进行了阐述,提出了一种基于激光点云数据的无人驾驶航空器空中走廊构建技术。采用噪声水平估计模型对数字表面模型的噪声幅度进行估计,应用高斯滤波器对标记的噪声区域进行噪声抑制。构建经验分解模型,对滤波后的数字表面模型进行能量分解,生成固有模态函数和残差信号,结合基于坡度的阈值模型,识别非地表目标,生成数字地势模型。采用数字表面模型和数字地势模型,对低空空域进行空域分层处理,将低空空域划分为顶层区、安全区和起降区三层空域。采用地理位置数据映射方式,将非地表物体和个人隐私保护区域,映射到划分后的各层空域,结合飞行路径规划技术,避开飞行期间的个人隐私保护区和限制飞行区。最后,采用可视化技术实现低空空域空中走廊的三维构建。实验结果表明,该空中走廊的构建方法能够提高飞行区域地物目标的识别精度,实现个人隐私保护,对低空安全产业发展具有积极的意义。

Abstract:

The low altitude safety and privacy protection were illustrated and the construction of aerial corridor for unmanned aircraft system in low altitude airspace based on point cloud of laser scanner was proposed. The noise amplitude of digital surface model was estimated by noise level model and the Gaussian filter was used to perform the noise suppression for the marked noise area. The empirical model decomposition method was designed to implement the extraction of energy to produce the intrinsic mode functions and the residual signal. Combined with the threshold model based on the slope range, non-ground objects were distinguished, and digital terrain model was constructed. Low altitude airspace was divided into three zones, namely upper zone, safe zone, and takeoff landing zone based on the above digital surface model and digital terrain model. Aimed at nonground objects and privacy protection areas, the geographic datasets were mapped to the divided zones, the privacy protection areas and restriction areas were avoided based on flight path planning technology. Finally, the visualization technology was adopted to perform the three-dimensional construction of aerial corridor in low altitude airspace. The experiments showed the recognition accuracy of the ground objects in flight areas was improved based on the aerial corridor, the privacy protection was achieved, which has positive significance to the development of low altitude safety industry.