A hyperspectral lidar system (HSL) dedicated to underwater detection is studied. Using a white light laser combined with a tunable filter as a light source, the integrated detection of ranging information and spectral information of underwater targets is realized. The system has the echo detection capability of 160 channels in 450nm-610nm wavelength, and the spectral resolution is 10nm. Substance differentiation was achieved by testing different underwater targets, including sponges, ferromanganese crusts, titanomagnetite, and apatite. The underwater application of hyperspectral lidar is initially explored.
Generating colored point cloud by the fusion of CCD images and point cloud data can exert both of their superiorities sufficiently, which has been a major method to obtain spatial information of the buildings for building reconstruction, object detection and other applications. Airborne LiDAR and CCD cameras are usually combined on one platform to carry out colored point cloud based on registration. In addition, there is also a new 3D imaging sensor that can acquire point cloud and CCD images with a stable relationship by the mechanism of common optical system, which could generate colored point cloud faster than the former. In the process of fusion, the colored point cloud is possible to absence some building information such as corners and boundaries. Interpolation is an optimistic method to solve the above issue. However, due to the unclear boundaries between building and ground in the point cloud data, the elevation error of the building area is large after interpolation. Therefore, a correction method for the elevation of colored point cloud in building area is proposed in this paper by combining point cloud contour extraction, image region merging and contour regularization. The new method can accurately obtain the edge of the building by the using of stable relationship, thus reducing the elevation interpolation error of the colored point cloud. The effectiveness of the method is validated based on the flight test data of 3D imaging sensor. The accuracy is improved by 33% after elevation correction.
Satellite laser range system measures the distance between the satellite and the surface of the earth by figuring out the transit time of laser pulse. The beam is refracted when it goes through the atmosphere. The atmosphere refraction effect causes laser propagation delay and path bending, which is one of the key factors to restrict the accuracy of laser ranging. In order to improve the accuracy of atmospheric refraction delay correction, it is necessary to strengthen the study of atmospheric group refractivity models and atmospheric refraction delay correction method. According to the datum of Xuzhou upper air meteorological station, which are the monthly values of upper limit layers for 30 years (1981-2010) in China, three atmospheric group refractivity models were analyzed and compared. The atmospheric refraction delays to LiDAR were calculated by ray tracing method. The differences among the group refractivity models as a function of month and angle of direction were given, which lay the foundation for the practical application and precision evaluation of LiDAR.
KEYWORDS: LIDAR, 3D acquisition, 3D image processing, Imaging systems, 3D image reconstruction, Image resolution, Signal detection, Target detection, Image processing
To verify the performance of Ghost Image via Sparsity Constraints (GISC) LiDAR system and evaluate the distance accuracy, on the basis of considering the parameters of the GISC LiDAR system, the research on design, development and setting method of related target is carried out. The measuring accuracy of distance measurement is verified in the field test. The measurement data of the airborne platform loading load are obtained to evaluate the range accuracy of the GISC LiDAR system.
Satellite laser range system measures the distance between the satellite and the surface of the earth by figuring out the transit time of laser pulse. The beam is refracted when it goes through the atmosphere. The atmosphere refraction effect causes laser propagation delay and path bending, which is one of the key factors to restrict the accuracy of laser ranging. In order to improve the accuracy of atmospheric refraction delay correction, it is necessary to strengthen the study of atmospheric group refractivity models and atmospheric refraction delay correction method. According to the data of Xuzhou upper air meteorological station, which are the monthly values of upper limit layers for 30 years (1981-2010) in China, three atmospheric group refractivity models were analyzed and compared. The atmospheric refraction delays to LiDAR were calculated by ray tracing method. The differences among the group refractivity models as a function of month or direction angle were given, which lay the foundation for the practical application and precision evaluation of LiDAR.
A diode laser sensor based on absorption spectroscopy has been developed for the measurement of spectroscopic parameters of the R(50) line at 5007.787cm-1 (20012<-00001 band) of CO2. Survey spectra of the CO2 R(50) line of CO2 - CO mixture gas with 49.82% CO2 were recorded at different temperatures and pressures through a high temperature measurement system using tunable diode laser absorption spectroscopy. High-resolution measurements of the CO2 R(50) line shape were used to determine collisional broadening full-width of CO2 by CO as a function of pressure and temperature. The collisional broadening coefficients were obtained at temperatures between 323K and 1873K, and the temperature dependent coefficient of the collisional broadening full-width of CO2 by CO was calculated. These parameters are supplement and improvement to the existing database. They are helpful for the detection of CO2 concentration in combustion diagnosis to ensure the accurate inversion of CO2 concentration in the combustion process.
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