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NASA Visualization Explorer

Goddard Space Flight Center, Greenbelt, Maryland NASA Visualization Explorer (NASA Viz) is an intuitive, interactive iOS application (app) that delivers science stories with multimedia content linking high-quality explorable images, descriptive text, visualizations, videos, and interviews with a fresh look and feel. NASA Viz aims to excite a wide audience about Goddard’s research, science efforts, and talent, and educate the audience about NASA science in an informal, highly visual environment.

Posted in: Articles, Briefs, TSP, Electronics & Computers

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Simple Safe Site Selection (S4) Algorithm

This is a much more computationally efficient method for finding safe landing sites. NASA’s Jet Propulsion Laboratory, Pasadena, California This hazard avoidance algorithm uses a single flash lidar range image to select a safe landing site for NASA missions. The advantage of flash lidar is that the entire range image is captured instantaneously, and therefore, is trajectory-independent. This is unlike a scanning lidar on a moving vehicle, where ranges have to be assembled in spacetime to form a complete range image.

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Fast Classification Method for Multivariate Mixtures of Spectroscopic Responses

Method uses a large database composed of correlated predictors. NASA’s Jet Propulsion Laboratory, Pasadena, California In many fields of spectroscopy, classification of the measured multivariate response is not always a straightforward process. Accurate classification is limited by many factors that are highly dependent upon the spectroscopy method being utilized. In all cases, however, the classification process is complicated by the complexity of the multivariate response, the quality and size of the database being utilized, and the ever present, clouding contaminants of noise and undesired background. A new classification scheme addresses these complications with a very fast, simple, and easily implemented algorithm that allows one to easily and quite accurately identify individual features of spectroscopic mixtures. The method is applied to Raman spectroscopy with the use of the RRUFF database for classification of mineralogical mixtures acquired using a time-gated Raman spectrometer.

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Feature Database

NASA’s Jet Propulsion Laboratory, Pasadena, California The primary function of the Feature Database (FDB) is to contain information about all the ground features seen so far in a sequence of aerial images. This information is organized so that features can be efficiently located and tracked into later images. As each new image is processed, the database grows to include more images and more features. Feature tracking is a basic component of a number of general-purpose computer vision algorithms, with wide applicability in aeronautical and space activities such as terrain modeling, mapping, GPS-denied navigation, and geo-registration. The Feature Database extends feature tracking capabilities, and should enhance its use in these kinds of applications.

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DRAT: A Distributed Release Audit Tool

NASA’s Jet Propulsion Laboratory, Pasadena, California DRAT software overcomes limitations inherent in the Apache Release Audit Tool (RAT), and also brings code auditing and open-source license analysis into the realm of Big Data by using scalable, open-source Apache technologies. Distributed RAT (DRAT) leverages Apache Tika to automatically detect and classify files in source code repositories, and determines what in the code is a binary file, what is source code, what are notes that need skipping, etc.

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Peak-Seeking Control Method

An algorithm optimizes performance of complex operations in real time. Neil A. Armstrong Flight Research Center, Edwards, California Peak-seeking algorithms optimize physical processes in real time and are widely used throughout a variety of industries. However, measuring associated parameters in changing conditions, and responding to them appropriately, is difficult because the measurements are typically distorted by noise. This technology addresses that problem by employing a time-varying Kalman filter. The filter is an algorithm previously developed to estimate unknown parameters within systems that are intrinsically random and uncertain. The Kalman filter is excellent at finding estimates when it encounters noisy signals. As a minimal-variant filter, it inherently produces the best estimates of a function with the smallest amount of variation from the true value. Thus, the filter can help accurately determine the optimal coordinates of the peak- seeking function as conditions in the environment change.

Posted in: Briefs, TSP, Electronics & Computers

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Enterprise Middleware Solution

Neil A. Armstrong Flight Research Center, Edwards, California An enterprise middleware solution allows disparate information technology (IT) systems to be integrated into one seamless, efficient system. As software and database platforms continue to develop at an accelerated pace, legacy systems can be a drain on resources, requiring complex workarounds and major code modifications in order to share data. This middleware offers an easy-to-use tool that integrates existing IT systems with new applications to help businesses become more agile, intelligent, and innovative.

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