对大多机载激光雷达系统而言，都配有数字相机，可以在获取LIDAR点云数据的同时获得光学影像数据。光学图像的摄影测量与基于激光测距的激光雷达具有一定的互补性。为获得精度高、密度大、整体性好的地表三维数据，针对二者的优缺点，本题将激光雷达数据和基于摄影测量技术的光学图像联合起来，旨在来提高地表三维信息精度。 研究内容主要包括四部分：1）LIDAR数据与同步获取的光学影像联合处理方法探索。2）基于激光三维点云影像同名点匹配。3）多数据源系统联合平差模型的建立、简化及求解。4）LIDAR数据的应用实验及结果验证。 论文首先通过对LIDAR实际数据进行处理，详细了解了其数据格式。以此基础上，确立了LIDAR数据与同步获取的光学影像联合处理流程及方法。 之后，在LIDAR飞行系统同步获取影像的辅助下，对两影像前方交会所得三维点云以及基于同一场景的LIDAR点云数据（.las数据）进行了ICP匹配，得到优化后的影像外方位元素。实验结果表明，经ICP匹配后，两影像前方交会所得三维点云坐标在X、Y、Z方向上都以超过一个数量级的程度趋近实际激光点云坐标系统。 然后，基于优化后的影像外方位元素，联合LIDAR点云以及同步获取的影像，进行了同名点匹配。实验结果表明，通过联合二者可减小像元搜索范围，加快匹配速度，提高激光雷达点云匹配精度。 因实际测量数据受多种因素综合影响，不利于对某种误差影响因素独立研究。因此，论文同时建立了LIDAR模拟系统，既可解决数据来源问题，又可不受限制的改变系统参数进行研究。系统包括三个部分，外方位元素模拟、激光点云模拟以及影像模拟。 通过模拟系统获得 LIDAR点云与光学图像等数据，建立了多源数据方程组，以及最小二乘求解。经联合平差得到优化后的航迹瞬时位置和角元素。然后，将此航迹瞬时位置以及角元素输入到激光点云扫描系统中，模拟得到了优化的激光点三维坐标。 实验表明，通过将机载LIDAR模拟系统的点云数据与光学图像联合起来可优化影像外方位元素，减小像元搜索范围，提高同名点匹配精度与速度，进一步通过联合平差，提高地表三维信息精度。

For most of the airborne LIDAR systems, which are equipped with digital cameras, you can obtain the LIDAR point cloud data, while access to the optical image data. Photogrammetry based on optical images has a certain degree of complementarity with LIDAR. To obtain three-dimensional surface data with high accuracy, high density and good quality, addressing both advantages and disadvantages, LIDAR data and optical images based on photogrammetry are combined together to improve the accuracy of three-dimensional surface. This research mainly includes four parts: 1)Study of the combination ot LIDAR data and the optical images obtained at the same time.2)Research on fast image matching with LIDAR points assisted.3)Bundle adjustment of the model with multi-source data, simplifying and solving. 4)Experiments with LIDAR data and results’ verification. In this paper, LIDAR data measured was firstly studied with the result of the detail of its format. With this based on,the method of combining LIDAR data and the imagery together was established. Then, ICP matching between .las points and 3D points through intersection acquired at the same region was done with the auxiliary images assisted to achieve better images’ exterior orientation. Results shows, the 3D points’ coordination at each direction is closer to the LIDAR points at about 1-level degree after ICP matching. After that, Image matching with better images’ exterior orientation and LIDAR points assisted was achived. Result shows, the method of combining the two together is fast and with the high accuracy. However, the actual data affected by many factors which influence the error is not favorable for independent study of any factor contribution.Therefore, a virtual flight system is set as data sources which can solve the problem, and also the system parameters can be changed with no restriction. The LIDAR system consists of three parts, that are exterior orientation simulation, the laser point cloud simulation and image simulation. Thus, LIDAR points and images can be obtained through LIDAR simulation system. Combine them together, solve the equations through the method of the least square with the result of the adjusted spatial position and attitude of the trajectory. Finally, Recalculate the new and better accuracy of surface elevation with the adjustment results as an input to the LIDAR simulation system. Experiments show that,1）the method of imagery corresponding point matching with the auxiliary LIDAR points is fast and with the high accuracy.2）airborne LIDAR point cloud data through the bundle adjustment system combined with the optical image can improve the accuracy of three-dimensional surface information.