A novel three-dimensional（3D） imaging lidar system which is based on a virtual instrument technique is introduced in this paper. The main characteristics of the system include： the capability of modeling a 3D objec...A novel three-dimensional（3D） imaging lidar system which is based on a virtual instrument technique is introduced in this paper. The main characteristics of the system include： the capability of modeling a 3D object in accordance with the actual one by connecting to a geographic information system（GIS）, and building the scene for the lidar experiment including the simulation environment. The simulation environment consists of four parts： laser pulse, atmospheric transport,target interaction, and receiving unit. Besides, the system provides an interface for the on-site experiment. In order to process the full waveform, we adopt the combination of pulse accumulation and wavelet denoising for signal enhancement.We also propose an optimized algorithm for data decomposition： the V-L decomposition method, which combines Vondrak smoothing and laser-template based fitting. Compared with conventional Gaussian decomposition, the new method brings an improvement in both precision and resolution of data decomposition. After applying V-L decomposition to the lidar system, we present the 3D reconstructed model to demonstrate the decomposition method.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.608320036)
文摘A novel three-dimensional（3D） imaging lidar system which is based on a virtual instrument technique is introduced in this paper. The main characteristics of the system include： the capability of modeling a 3D object in accordance with the actual one by connecting to a geographic information system（GIS）, and building the scene for the lidar experiment including the simulation environment. The simulation environment consists of four parts： laser pulse, atmospheric transport,target interaction, and receiving unit. Besides, the system provides an interface for the on-site experiment. In order to process the full waveform, we adopt the combination of pulse accumulation and wavelet denoising for signal enhancement.We also propose an optimized algorithm for data decomposition： the V-L decomposition method, which combines Vondrak smoothing and laser-template based fitting. Compared with conventional Gaussian decomposition, the new method brings an improvement in both precision and resolution of data decomposition. After applying V-L decomposition to the lidar system, we present the 3D reconstructed model to demonstrate the decomposition method.
