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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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5 records
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NASA NTRS2020

Instrument Offset Optimization Technique for Airborne Doppler Wind Lidar Profiling Algorithm

This paper presents the instrument offset optimization technique for the Doppler Aerosol Wind Lidar (DAWN) profiling algorithm at NASA Langley Research Center (LaRC). The 2 um Doppler wind Lidar system at LaRC has a long history of research development and airborne campaigns. The core of the wind Lidar data processing is Airborne Wind Profiling Algorithm for Doppler Wind Lidar (APOLO), which was developed at LaRC. The extraction of wind parameters from the airborne Doppler wind Lidar data is challenging due to many factors such as the speed of aircraft, and the errors in instrument installation and calibration. It is unavoidable to prevent the adverse impact of calibration error and instrument installation offset on the performance of wind parameter estimation in the algorithm. Due to the unsteady environment where the data are collected, even a small offset will result in nonsensical results in the parameter estimation process. A brief introduction of APOLO and the overview of the optimization techniques are presented in this paper.

Wind profile↗
NASA NTRS2014

Offshore Wind Measurements Using Doppler Aerosol Wind Lidar (DAWN) at NASA Langley Research Center

The latest flight demonstration of Doppler Aerosol Wind Lidar (DAWN) at NASA Langley Research Center (LaRC) is presented. The goal of the campaign was to demonstrate the improvement of DAWN system since the previous flight campaign in 2012 and the capabilities of DAWN and the latest airborne wind profiling algorithm APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) developed at LaRC. The comparisons of APOLO and another algorithm are discussed utilizing two and five line-of-sights (LOSs), respectively. Wind parameters from DAWN were compared with ground-based radar measurements for validation purposes. The campaign period was June - July in 2013 and the flight altitude was 8 km in inland toward Charlotte, NC, and offshores in Virginia Beach, VA and Ocean City, MD. The DAWN system was integrated into a UC12B with two operators onboard during the campaign.

Beyon, Jeffrey Y.↗
NASA NTRS2013

Airborne Wind Profiling Algorithms for the Pulsed 2-Micron Coherent Doppler Lidar at NASA Langley Research Center

Two versions of airborne wind profiling algorithms for the pulsed 2-micron coherent Doppler lidar system at NASA Langley Research Center in Virginia are presented. Each algorithm utilizes different number of line-of-sight (LOS) lidar returns while compensating the adverse effects of different coordinate systems between the aircraft and the Earth. One of the two algorithms APOLO (Airborne Wind Profiling Algorithm for Doppler Wind Lidar) estimates wind products using two LOSs. The other algorithm utilizes five LOSs. The airborne lidar data were acquired during the NASA's Genesis and Rapid Intensification Processes (GRIP) campaign in 2010. The wind profile products from the two algorithms are compared with the dropsonde data to validate their results.

Beyon, Jeffrey Y.↗
NASA NTRS2015

Airborne Doppler Wind Lidar Post Data Processing Software DAPS-LV

Systems, methods, and devices of the present invention enable post processing of airborne Doppler wind LIDAR data. In an embodiment, airborne Doppler wind LIDAR data software written in LabVIEW may be provided and may run two versions of different airborne wind profiling algorithms. A first algorithm may be the Airborne Wind Profiling Algorithm for Doppler Wind LIDAR ("APOLO") using airborne wind LIDAR data from two orthogonal directions to estimate wind parameters, and a second algorithm may be a five direction based method using pseudo inverse functions to estimate wind parameters. The various embodiments may enable wind profiles to be compared using different algorithms, may enable wind profile data for long haul color displays to be generated, may display long haul color displays, and/or may enable archiving of data at user-selectable altitudes over a long observation period for data distribution and population.

Beyon, Jeffrey Y.↗
NASA NTRS2008

Improved Linear Algebra Methods for Redshift Computation from Limited Spectrum Data - II

Given photometric broadband measurements of a galaxy, Gaussian processes may be used with a training set to solve the regression problem of approximating the redshift of this galaxy. However, in practice solving the traditional Gaussian processes equation is too slow and requires too much memory. We employed several methods to avoid this difficulty using algebraic manipulation and low-rank approximation, and were able to quickly approximate the redshifts in our testing data within 17 percent of the known true values using limited computational resources. The accuracy of one method, the V Formulation, is comparable to the accuracy of the best methods currently used for this problem.

Foster, Leslie↗