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Active Aircraft Pylon Noise Control System
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Method of Bonding Dissimilar Materials
Sonar Inspection Robot System
Applying the Dynamic Inertia Measurement Method to Full-Scale Aerospace Vehicles
Method and Apparatus for Measuring Surface Air Pressure
Fully Premixed, Low-Emission, High-Pressure, Multi-Fuel Burner
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Tool for Statistical Analysis and Display of Landing Sites

MarsLS is a software tool for analyzing statistical dispersion of spacecraft-landing sites and displaying the results of its analyses. Originally intended for the Mars Explorer Rover (MER) mission, MarsLS is also applicable to landing sites on Earth and non-MER sites on Mars. MarsLS is a collection of interdependent MATLAB scripts that utilize the MATLAB graphical-user- interface software environment to display landing-site data (see figure) on calibrated image-maps of the Martian or other terrain. The landing- site data comprise latitude/longitude pairs generated by Monte Carlo runs of other computer programs that simulate entry, descent, and landing. Using these data, MarsLS can compute a landing-site ellipse — a standard means of depicting the area within which the spacecraft can be expected to land with a given probability. MarsLS incorporates several features for the user’s convenience, including capabilities for drawing lines and ellipses, overlaying kilometer or latitude/longitude grids, drawing and/or specifying lines and/or points, entering notes, defining and/or displaying polygons to indicate hazards or areas of interest, and evaluating hazardous and/or scientifically interesting areas. As part of such an evaluation, MarsLS can compute the probability of landing in a specified polygonal area.

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Automated Assignment of Proposals to Reviewers

A computer program automates the process of selecting unbiased peer reviewers of research proposals submitted to NASA. Heretofore, such selection has been performed by manual searching of two large databases subject to a set of assignment rules. One database lists proposals and proposers; the other database lists potential reviewers. The manual search takes an average of several weeks per proposal. In contrast, the present software can perform the selection in seconds. The program begins by selecting one entry from each database, then applying the assignment rules to this pair of entries. If and only if all the assignment rules are satisfied, the chosen reviewer is assigned to the chosen proposal. The assignment rules enforced by the program are (1) a maximum allowable number of proposals assigned to a single reviewer; (2) a maximum allowable number of reviewers assigned to a single proposal; (3) if the proposing team includes a member affiliated with an industry, then the reviewer must not be affiliated with any industry; and (4) the reviewer must not be a member of the proposing team or affiliated with the same institution as that of a member of the proposing team.

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Array-Pattern-Match Compiler for Opportunistic Data Analysis

A computer program has been written to facilitate real-time sifting of scientific data as they are acquired to find data patterns deemed to warrant further analysis. The patterns in question are of a type denoted array patterns, which are specified by nested parenthetical expressions. [One example of an array pattern is ((>3) 0 (≠1)): this pattern matches a vector of at least three elements, the first of which exceeds 3, the second of which is 0, and the third of which does not equal 1.] This program accepts a high-level description of a static array pattern and compiles a highly optimal and compact other program to determine whether any given instance of any data array matches that pattern. The compiler implemented by this program is independent of the target language, so that as new languages are used to write code that processes scientific data, they can easily be adapted to this compiler. This program runs on a variety of different computing platforms. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware.

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Pre-Processor for Compression of Multispectral Image Data

A computer program that preprocesses multispectral image data has been developed to provide the Mars Exploration Rover (MER) mission with a means of exploiting the additional correlation present in such data without appreciably increasing the complexity of compressing the data. When used in conjunction with ICER, a previously developed image-data-compression program, this program enables improved compression of multispectral images, compared to that achievable by use of ICER alone. As such, it is a straightforward means of achieving much of the gain possible from exploiting spectral correlation. This preprocessor software accommodates up to seven images that are different spectral bands of the same scene. The software performs an approximate discrete cosine transform (DCT) pixelwise across the spectral bands. The software is written for speed; in particular the DCT operation performs only integer operations (producing integer output) and uses multiplications sparingly. Separate code is used for each possible number of spectral bands, including numbers for which fast DCT functions are not normally implemented. The DCT output is scaled so that, if the original images have a bit depth of at most 12, the transformed images are guaranteed to have a dynamic range appropriate for compression by the ICER software on the MER rovers. The resulting transformed bands are compressed individually by ICER. To reconstruct the images, the transformed images are first decompressed by use of the decompressor for ICER, then the resulting reconstructed images are passed to an inverse-DCT subprogram, which reconstructs the various spectral bands.

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Compressing Image Data While Limiting the Effects of Data Losses

ICER is computer software that can perform both lossless and lossy compression and decompression of gray-scaleimage data using discrete wavelet transforms. Designed for primary use in transmitting scientific image data from distant spacecraft to Earth, ICER incorporates an error-containment scheme that limits the adverse effects of loss of data and is well suited to the data packets transmitted by deep-space probes. The error-containment scheme includes utilization of the algorithm described in “Partitioning a Gridded Rectangle Into Smaller Rectangles” (NPO-30479), NASA Tech Briefs, Vol. 28, No. 7 (July 2004), page 56. ICER has performed well in onboard compression of thousands of images transmitted from the Mars Exploration Rovers.

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Flight Operations Analysis Tool

Flight Operations Analysis Tool (FLOAT) is a computer program that partly automates the process of assessing the benefits of planning spacecraft missions to incorporate various combinations of launch vehicles and payloads (see figure). Designed primarily for use by an experienced systems engineer, FLOAT makes it possible to perform a preliminary analysis of trade-offs and costs of a proposed mission in days, whereas previously, such an analysis typically lasted months. FLOAT surveys a variety of prior missions by querying data from authoritative NASA sources pertaining to 20 to 30 mission and interface parameters that define space missions. FLOAT provides automated, flexible means for comparing the parameters to determine compatibility or the lack thereof among payloads, spacecraft, and launch vehicles, and for displaying the results of such comparisons. Sparseness, typical of the data available for analysis, does not confound this software. FLOAT effects an iterative process that identifies modifications of parameters that could render compatible an otherwise incompatible mission set.The Database Overview shows current and future capabilities.

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Improvement in Visual Target Tracking for a Mobile Robot

In an improvement of the visual-targettracking software used aboard a mobile robot (rover) of the type used to explore the Martian surface, an affine-matching algorithm has been replaced by a combination of a normalized-cross- correlation (NCC) algorithm and a template-image- magnification algorithm. Although neither NCC nor template-image magnification is new, the use of both of them to increase the degree of reliability with which features can be matched is new. In operation, a template image of a target is obtained from a previous rover position, then the magnification of the template image is based on the estimated change in the target distance from the previous rover position to the current rover position (see figure). For this purpose, the target distance at the previous rover position is determined by stereoscopy, while the target distance at the current rover position is calculated from an estimate of the current pose of the rover. The template image is then magnified by an amount corresponding to the estimated target distance to obtain a best template image to match with the image acquired at the current rover position.Turn-in-Place Experiments show beginning image (left) and end image (right) after 80° rover rotation. As the rover turns, the mast camera turns in the opposite direction to point to the target.

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