Integrierte Georeferenzierung für bildgebende Systeme mit sequentieller Datenakquisition

该项目的目标是开发从移动平台获取的激光扫描仪和相机数据的综合地理参考方法。虽然激光扫描仪和相机数据的处理允许内部厘米精度，但车辆位置和姿态传感器通常不太精确，因此不允许充分的地理参考。这对于诸如移动的机器人或UAV（无人驾驶飞行器）等领域是典型的。由于激光扫描仪数据采集的顺序方式，对轨迹表示的时间分辨率要求很高，这进一步阻碍了地理参考过程，因此，平台位置和定向参数应通过综合光束法平差程序确定。由于缺乏时间分辨率，光束法平差不能纯粹基于相机图像。相反，时间分辨的参数化平台轨迹作为未知数引入到调整中。通过在综合光束法平差中引入激光扫描仪测量值来支持轨迹确定。在光束法平差程序中整合图像和laserscanner数据还需要开发用于确定图像和laserscanner数据中的同源特征的技术，以及开发用于自适应平衡不同观测类别权重的随机模型。

The goal of the project is the development of methods for an integrated georeferencing of laserscanner and camera data acquired from a moving platform. While the processing of the laserscanner and camera data allows for internal centimeter-accuracy, the vehicle position and attitude sensorics will often be much less precise and will thus not allow for adequate georeferencing. This is typical for areas such as mobile robotics or UAVs (unmanned aerial vehicles). The georeferencing process is further impeded by high requirements concerning the temporal resolution of the trajectory representation due to the sequential manner of laserscanner data acquisition.Therefore, the platform position and orientation parameters shall be determined by an integrated bundle adjustment procedure. Due to the lack of temporal resolution, the bundle adjustment cannot purely be based on the camera images. Instead, a time-resolved parameterized platform trajectory is introduced as an unknown into the adjustment. The trajectory determination is supported by introducing laserscanner measurements in the integrated bundle adjustment. Integrating image and laserscanner data in a bundle adjustment procedure also requires the development of techniques for the determination of homologous features in the image and laserscanner data as well as the development of stochastic models for an adaptive balancing of the weights of the different observation classes.