The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform
Martin Krůček - One of the best experts on this subject based on the ideXlab platform.
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New Opportunities for Forest Remote Sensing Through Ultra-High-Density Drone Lidar
Surveys in Geophysics, 2019Co-Authors: James R. Kellner, Markus Birrer, K. C. Cushman, Laura Duncanson, Christoph Eck, Christoph Falleger, Benedikt Imbach, John Armston, Kamil Král, Martin KrůčekAbstract:Current and planned space missions will produce aboveground biomass density data products at varying spatial resolution. Calibration and validation of these data products is critically dependent on the existence of field estimates of aboveground biomass and coincident remote sensing data from airborne or terrestrial lidar. There are few places that meet these requirements, and they are mostly in the northern hemisphere and temperate zone. Here we summarize the potential for low-altitude Drones to produce new observations in support of mission science. We describe technical requirements for producing high-quality measurements from autonomous platforms and highlight differences among commercially available laser scanners and Drone Aircraft. We then describe a case study using a heavy-lift autonomous helicopter in a temperate mountain forest in the southern Czech Republic in support of calibration and validation activities for the NASA Global Ecosystem Dynamics Investigation. Low-altitude flight using Drones enables the collection of ultra-high-density point clouds using wider laser scan angles than have been possible from traditional airborne platforms. These measurements can be precise and accurate and can achieve measurement densities of thousands of points · m^−2. Analysis of surface elevation measurements on a heterogeneous target observed 51 days apart indicates that the realized range accuracy is 2.4 cm. The single-date precision is 2.1–4.5 cm. These estimates are net of all processing artifacts and geolocation errors under fully autonomous flight. The 3D model produced by these data can clearly resolve branch and stem structure that is comparable to terrestrial laser scans and can be acquired rapidly over large landscapes at a fraction of the cost of traditional airborne laser scanning.
Kenneth Fisher - One of the best experts on this subject based on the ideXlab platform.
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Air-to-air missile vector scoring
2011 IEEE International Conference on Control Applications (CCA), 2011Co-Authors: Nicholas Sweeney, Kenneth FisherAbstract:An air-to-air missile vector scoring system is proposed for test and evaluation applications. A linear six-state constant velocity (CV) dynamics model is used, consisting of missile position and velocity in a Cartesian coordinate system. Frequency modulated continuous wave (FMCW) radar sensors, carefully located to provide spherical coverage around the target, provide updates of missile kinematic information relative to a Drone Aircraft. Data from the radar sensors are linearized about a nominal measurement and fused with missile model predictions using an extended Kalman filter (EKF) algorithm. The performance of the system is evaluated through high-fidelity, six-degree of freedom (6DOF) simulations yielding sub-meter end-game accuracy in a variety of scenarios.
Nicholas Sweeney - One of the best experts on this subject based on the ideXlab platform.
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CCA - Air-to-air missile vector scoring
2011 IEEE International Conference on Control Applications (CCA), 2011Co-Authors: Nicholas Sweeney, Kenneth A. FisherAbstract:An air-to-air missile vector scoring system is proposed for test and evaluation applications. A linear six-state constant velocity (CV) dynamics model is used, consisting of missile position and velocity in a Cartesian coordinate system. Frequency modulated continuous wave (FMCW) radar sensors, carefully located to provide spherical coverage around the target, provide updates of missile kinematic information relative to a Drone Aircraft. Data from the radar sensors are linearized about a nominal measurement and fused with missile model predictions using an extended Kalman filter (EKF) algorithm. The performance of the system is evaluated through high-fidelity, six-degree of freedom (6DOF) simulations yielding sub-meter end-game accuracy in a variety of scenarios.
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Air-to-air missile vector scoring
2011 IEEE International Conference on Control Applications (CCA), 2011Co-Authors: Nicholas Sweeney, Kenneth FisherAbstract:An air-to-air missile vector scoring system is proposed for test and evaluation applications. A linear six-state constant velocity (CV) dynamics model is used, consisting of missile position and velocity in a Cartesian coordinate system. Frequency modulated continuous wave (FMCW) radar sensors, carefully located to provide spherical coverage around the target, provide updates of missile kinematic information relative to a Drone Aircraft. Data from the radar sensors are linearized about a nominal measurement and fused with missile model predictions using an extended Kalman filter (EKF) algorithm. The performance of the system is evaluated through high-fidelity, six-degree of freedom (6DOF) simulations yielding sub-meter end-game accuracy in a variety of scenarios.
James R. Kellner - One of the best experts on this subject based on the ideXlab platform.
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New Opportunities for Forest Remote Sensing Through Ultra-High-Density Drone Lidar
Surveys in Geophysics, 2019Co-Authors: James R. Kellner, Markus Birrer, K. C. Cushman, Laura Duncanson, Christoph Eck, Christoph Falleger, Benedikt Imbach, John Armston, Kamil Král, Martin KrůčekAbstract:Current and planned space missions will produce aboveground biomass density data products at varying spatial resolution. Calibration and validation of these data products is critically dependent on the existence of field estimates of aboveground biomass and coincident remote sensing data from airborne or terrestrial lidar. There are few places that meet these requirements, and they are mostly in the northern hemisphere and temperate zone. Here we summarize the potential for low-altitude Drones to produce new observations in support of mission science. We describe technical requirements for producing high-quality measurements from autonomous platforms and highlight differences among commercially available laser scanners and Drone Aircraft. We then describe a case study using a heavy-lift autonomous helicopter in a temperate mountain forest in the southern Czech Republic in support of calibration and validation activities for the NASA Global Ecosystem Dynamics Investigation. Low-altitude flight using Drones enables the collection of ultra-high-density point clouds using wider laser scan angles than have been possible from traditional airborne platforms. These measurements can be precise and accurate and can achieve measurement densities of thousands of points · m^−2. Analysis of surface elevation measurements on a heterogeneous target observed 51 days apart indicates that the realized range accuracy is 2.4 cm. The single-date precision is 2.1–4.5 cm. These estimates are net of all processing artifacts and geolocation errors under fully autonomous flight. The 3D model produced by these data can clearly resolve branch and stem structure that is comparable to terrestrial laser scans and can be acquired rapidly over large landscapes at a fraction of the cost of traditional airborne laser scanning.
Markus Birrer - One of the best experts on this subject based on the ideXlab platform.
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New Opportunities for Forest Remote Sensing Through Ultra-High-Density Drone Lidar
Surveys in Geophysics, 2019Co-Authors: James R. Kellner, Markus Birrer, K. C. Cushman, Laura Duncanson, Christoph Eck, Christoph Falleger, Benedikt Imbach, John Armston, Kamil Král, Martin KrůčekAbstract:Current and planned space missions will produce aboveground biomass density data products at varying spatial resolution. Calibration and validation of these data products is critically dependent on the existence of field estimates of aboveground biomass and coincident remote sensing data from airborne or terrestrial lidar. There are few places that meet these requirements, and they are mostly in the northern hemisphere and temperate zone. Here we summarize the potential for low-altitude Drones to produce new observations in support of mission science. We describe technical requirements for producing high-quality measurements from autonomous platforms and highlight differences among commercially available laser scanners and Drone Aircraft. We then describe a case study using a heavy-lift autonomous helicopter in a temperate mountain forest in the southern Czech Republic in support of calibration and validation activities for the NASA Global Ecosystem Dynamics Investigation. Low-altitude flight using Drones enables the collection of ultra-high-density point clouds using wider laser scan angles than have been possible from traditional airborne platforms. These measurements can be precise and accurate and can achieve measurement densities of thousands of points · m^−2. Analysis of surface elevation measurements on a heterogeneous target observed 51 days apart indicates that the realized range accuracy is 2.4 cm. The single-date precision is 2.1–4.5 cm. These estimates are net of all processing artifacts and geolocation errors under fully autonomous flight. The 3D model produced by these data can clearly resolve branch and stem structure that is comparable to terrestrial laser scans and can be acquired rapidly over large landscapes at a fraction of the cost of traditional airborne laser scanning.
