Ove Steinvall received his MS degree in physics at the University of Uppsala in 1969. He was then employed by the National Defence Res. Establishment (FOA, now FOI) in 1969 where he worked on fast gas discharges for lasers and other applications. He received his Ph.D.in 1974 from Chalmers Institute of Technology in Lasers and Electro-Optics. Since 1977 he has been leading the Laser group, from 1994 as a Dpt Head and from 2007 as head of Optronic Systems Dpt., In 1991 he was appointed Research Director. His research activities include lasers, lasers for countermeasures, laser warning, laser radar /lidar including systems for imaging and mapping, free space laser communications and ocean /atmospheric optics. He is author or coauthor of about 100 conference and journal articles and about 300 internal reports. Dr. Steinvall is a member of SPIE, Society for Photo-Optical Instrumentation Engineers, Optical Society of America, Swedish Optical Society and the Royal Academy of Military Sciences. He has received 3 national rewards for his laser work. He has also received the NATO Scientific Achievement Award (SET-077). He was the conference chair for the international Topical Meeting on Coherent Laser Radars in Linköping Sweden, June 1997 and the co-chair for the European SPIE Aerosense Conference in Stockholm Sept. 2006 and a chair of the OSA meeting on Laser Sensing and Communications, Paris 2013.He is an expert in EDA Captech IAP3 and holds a position as Ass. Professor at Chalmers Institute of Technology. Dr. Steinvall is an expert in EDA Captech IAP3 and a SPIE fellow.
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The potential role of lasers in combating UAVs, part 1: detection, tracking, and recognition of UAVs
Laser range profiling is attractive because it can be seen as an extension from an ordinary laser range finder. The same laser can also be used for active imaging when the target comes closer and is angular resolved. This paper will discuss laser profiling for target recognition both as a standalone method and in combination with low transverse resolution imaging. Example of both simulated and experimental data for stationary and in flight targets will be investigated and analyzed for target classification purposes.
Laser range profiling is attractive because the maximum range can be substantial, especially for a small laser beam width. A range profiler can also be used in a scanning mode to detect targets within a certain sector and can also be used for active imaging when the target comes closer and is angular resolved. Although the profiling may by itself be sufficient for target classification the discrimination capabilities among a group of anticipated targets candidates may be uncertain due to uncertainty in the target aspect angles, atmospheric effects and sensor limitations. It is therefore motivated to look at a sensor fusion approach in which the profiling data is combined with imaging data even when these data have a rather low resolution. Example of both simulated and experimental data will be investigated and analyzed for target classification purposes.
The measurement was concentrated on low clouds, mostly of the cumulus type. We found that these clouds between 0-2 km often showed a layered structure and that they often indicated a limited optical density probably allowing for observation through the cloud. This information is hard to achieve from a passive EO sensor only. This was supported both from the simulation of the lidar response from thin clouds and from inverting the measured lidar waveform.
The comparison between the camera image intensities and the integrated range corrected lidar signals showed both negative and positive correlations. The highest positive correlation was obtained from comparing the lidar signal with the cloud temperature as derived from the FLIR camera. However, there were many cases when one or two of the camera intensities correlated negatively with the lidar signal. We could for example observe that under certain conditions the cloud which was dark in the SWIR appeared as white in the visible camera and vice versa. Example of lidar and image data will be presented and analyzed.
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