| Airborne mapping is a cutting-edge mapping technology that integrates various sensors,global positioning modules and inertial navigation modules in a pod,acheving ground measurement with unmanned aerial platforms.It has advantages such as high degree of automation,little weather influence,fast and accurate mapping,high efficiency and low cost.With the continuous development of theory and technical research in recent years,airborne mapping has been widely applied to island and coastal zone surveying,topography surveying,water conservancy and traffic surveying and so on.Combining lidar measurement technology,image measurement technology,global positioning and navigation technology and inertial navigation technology,an high-precision airborne mapping system is designed and implement in this paper.Besides,several joint calibration methods of sensor external parameter and methods of measuring sensor time delay are proposed and realized to reduce the error of mapping in this paper.In addition,based on the 3D measurement of lidar and the feature measurement of image,a performance optimization method for mapping that combines lidar data and image data is proposed in this paper,and then experiments verifies its effectiveness.The main contents of this paper are as follows:(1)According to the overall design of the airborne mapping system,an airborne mapping instrument that integrates multiple sensors is designed and implemented from the aspects of machinery,hardware,software,etc.,which realizes the data acquisition,storage and transmission of the sensors.Besides,a ground workstation software system is designed and implemented,which realized the remote control of the mapping instrument,synchronization of data reception,joint calibration of sensors and optimization of mapping point cloud.(2)Derives the point cloud generation model and rendering model according to the definition of the relevant coordinate system,and analyzes the error source of the point cloud generation and rendering effect.Besides,several joint calibration methods of sensor external parameters are proposed and implemented to calibrate the sensor external parameters; several sensor time delay measurement methods are proposed and implemented to synchronize the sensor data.Experiments have proved that the joint calibration methods of external sensor parameters and the measurement methods of sensor time delay can effectively reduce the point cloud generation model error and time synchronization error.(3)A mapping performance optimization method combining lidar data and image data is proposed and implemented in this paper.This method constructs an initial surveying point cloud through lidar mapping point cloud initialization and image mapping point cloud initialization,and constructs lidar mapping observation errors,image mapping observation errors and lidarimage fusion mapping observation error realizes the optimization of the mapping pose,and then optimizes the overall mapping results and improves mapping performance.Experiments show that the optimization method of mapping can effectively reduce the thickness of surveying and mapping point clouds. |
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