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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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At least 73 records · Page 4

Spatial, High-Accuracy, Positioning-Encoding Sensor (SHAPES) for large space system control applications

The Spatial, High-Accuracy, Position-Encoding Sensor is a controls sensor suitable for the determination of the static shape and vibrational motion of large space structures and similar systems and for the determination of position and velocity in rendezvous and docking. It uses a combination of electro-optical techniques to measure the three-dimensional coordinates distributed over the structure at reading rates high compared to the rates at which the coordinates are changing. The technical approach is that of measuring the distance to and the direction of points on the structure from a single sensor head. Many points can be measured simultaneously from a single head without significantly increasing the complexity of the system.

Mclauchlan, J. M.↗

Evaluation of space SAR as a land-cover classification

The multidimensional approach to the mapping of land cover, crops, and forests is reported. Dimensionality is achieved by using data from sensors such as LANDSAT to augment Seasat and Shuttle Image Radar (SIR) data, using different image features such as tone and texture, and acquiring multidate data. Seasat, Shuttle Imaging Radar (SIR-A), and LANDSAT data are used both individually and in combination to map land cover in Oklahoma. The results indicates that radar is the best single sensor (72% accuracy) and produces the best sensor combination (97.5% accuracy) for discriminating among five land cover categories. Multidate Seasat data and a single data of LANDSAT coverage are then used in a crop classification study of western Kansas. The highest accuracy for a single channel is achieved using a Seasat scene, which produces a classification accuracy of 67%. Classification accuracy increases to approximately 75% when either a multidate Seasat combination or LANDSAT data in a multisensor combination is used. The tonal and textural elements of SIR-A data are then used both alone and in combination to classify forests into five categories.

Brisco, B.↗

Shifting the Inertial Navigation Paradigm with MEMS Technology

Why don t you use MEMS? is one of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the specific error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary applications to Constellation vehicles will be explored.

Crain, Timothy↗

Shifting the Intertial Navigation Paradigm with the MEMS Technology

"Why don't you use MEMS?" is of the most common questions posed to navigation systems engineers designing inertial navigation solutions in the modern era. The question stems from a general understanding that great strides have been made in terrestrial MEMS accelerometers and attitude rate sensors in terms of accuracy, mass, and power. Yet, when compared on a unit-to-unit basis, MEMS devices do not provide comparable performance (accuracy) to navigation grade sensors in several key metrics. This paper will propose a paradigm shift where the comparison in performance is between multiple MEMS devices and a single navigation grade sensor. The concept is that systematically, a sufficient number of MEMS sensors may mathematically provide comparable performance to a single navigation grade device and be competitive in terms power and mass allocations when viewed on a systems level. The implication is that both inertial navigation system design and fault detection, identification, and recovery could benefit from a system of MEMS devices in the same way that swarm sensing has benefited Earth observation and astronomy. A survey of the state of the art in inertial sensor accuracy scaled by mass and power will be provided to show the scaled error in MEMS and navigation graded devices, a mathematical comparison of multi-unit to single-unit sensor errors will be developed, and preliminary application to an Orion lunar skip atmospheric entry trajectory will be explored.

Crain, Timothy P., II↗

Considerations for Optimal Sensor Placement for Higher Accuracy Object Localization for Urban Air Mobility

Previous research into object localization has shown that sensor placement and alignment plays an important role in achieving higher accuracy levels of the estimated location of a tracked Urban Air Mobility Vehicle. In general, a near-orthogonal intersection between the ground node observation vectors results in the highest accuracy due to a smaller overlapping uncertainty region between both. This applies to triangulation by means of ground node camera angle observations as well as trilateration by means of ground node distance measurements. However, this simple concept is not easily fulfilled with a network of a limited number of static ground nodes and a moving object to be localized. This case study performs sensitivity analyses and explores practical ways on how to achieve higher estimate accuracy levels in this context.

sensor placement↗

Considerations for Optimal Sensor Placement for Higher Accuracy Object Localization for Urban Air Mobility

Previous research into object localization has shown that sensor placement and alignment plays an important role in achieving higher accuracy levels of the estimated location of a tracked Urban Air Mobility Vehicle. In general, a near-orthogonal intersection between the ground node observation vectors results in the highest accuracy due to a smaller overlapping uncertainty region between both. This applies to triangulation by means of ground node camera angle observations as well as trilateration by means of ground node distance measurements. However, this simple concept is not easily fulfilled with a network of a limited number of static ground nodes and a moving object to be localized. This case study performs sensitivity analyses and explores practical ways on how to achieve higher estimate accuracy levels in this context.

sensor placement↗

Precision attitude determination for multimission spacecraft

Attitude determination algorithms for a multimission spacecraft are derived and their performance analyzed. The attitude determination system is composed of a strapdown Inertial Reference Unit (IRU), two fixed head star trackers, and an onboard computer. IRU data is processed to maintain real-time knowledge of spacecraft attitude relative to an inertial reference frame. Star tracker data is processed using Kalman filtering techniques to estimate and correct the attitude determination errors and the gyro drift compensation errors. The results of a star availability analysis for stellar, solar and earth pointing missions are presented. Linear covariance analysis techniques are used to evaluate nominal attitude determination performance, the effects of sensor measurement accuracy variations, the effects of errors in knowledge of sensor measurement accuracy, and the effects of star tracker misalignment errors. Results of a nonlinear simulation analysis of attitude determination performance are also presented. These analyses show that precision attitude determination for stellar, solar and earth pointing missions is achieved.

Murrell, J. W.↗

SHAPES - Spatial, high-accuracy, position-encoding sensor

Future space systems will require control sensors capable of real-time measurements of position coordinates of many structural locations. Applications for such a sensor include figure and vibration control, rendezvous and docking, and structure assembly verification. The paper discusses an experimental study of SHAPES (spatial, high-accuracy, position-encoding sensor), a 3D position sensor that provides range and two angular positions of laser-illuminated retroreflector targets that mark the locations to be measured. Simultaneous range measurements to multiple targets by a time-of-flight corelation of short laser pulses are made with a CCD-equipped streak tube. Angular positions are measured with a CCD camera. Position measurements of 24 targets with sub-millimeter range accuracy at a 10 Hz update rate have been demonstrated.

Nerheim, Noble M.↗

Impact of Thematic Mapper Sensor Characteristics on Classification Accuracy

A fixed effect, three factor (two levels per factor) analysis of variance was used to quantitatively assess the significance of the improved spectral, spatial and radiometric resolution capabilities of the LANDSAT-4 thematic mapper sensor relative to the familiar MSS sensor. TM data acquired over the Washington, D.C. area were progressively degraded in spectral, spatial and radiometric characteristics to simulate the MSS, and classification accuracies were derived in a consistent manner for all eight treatments in the ANOVA design. Statistical testing of the significance of differences in classification accuracies between treatments indicated that the increased number of spectral bands and the improved quantization capabilities afforded by the TM sensor design would lead to significant improvements in classification accuracies attainable relative to MSS. In contrast, however, the improved spatial resolution provided by the TM sensor did not enhance classification accuracy. This latter result was felt to be more a function of the type of classification algorithms available.

Williams, D. L.↗

Maximum theoretical angular accuracy of planar and linear arrays of sensors

The maximum theoretical accuracy in the angular location of a radiating object that can be obtained by using a planar or linear array is studied. The elements are assumed to have identical radiation patterns and the complex voltages observed at their ports are assumed to be subject to phase measurement errors, having normal probability density. An optimum scheme for the statistical extraction of the parameters defining the direction is established noting that the presence of thermal noise does not affect the structure of the estimator. Comparisons with the conventional multiple interferometric techniques are made.

Borgiotti, G. V.↗

Data sets and products

Against background of spacecraft and in situ measurements, participants at the JPL workshops sought to review the sensor performance, understand the different SSt retrieval algorithms, evaluate the sensor SST accuracies, and discuss directions for future sensor development. The issue of utilization of satellite SSTs in climate, air sea interaction, and mesoscale oceanography studies was not the main focus of the workshops, but did have a bearing on the recommendations that arose from the discussions. More date were available for analysis with the acquisition of AVHRR (MCSST), HIRS/MSU, and VAS data sets. In Workshop 3 the acquisition and analysis fo data were completed, recommendations for future research and sensor development were discussed, and plans were made for eventual publication of results from the workshop series in the open literature.

Hilland, J. E.↗

Impact of Thematic Mapper Sensor Characteristics on Classification Accuracy

A three factor (spectral, spatial, and radiometric resolution), two level (TM and MSS) analysis of variance (ANOVA) approach allowed evaluation of the effects of each factor individually and in all possible combinations. Digital classification accuracy was used as the figure of merit. Nine study sites in Washington, D.C. each of approximately 256 x 256 TM pixels, were randomly selected from the full scene for analysis. These results strongly suggest that the quantization level improvements and the addition of new spectral bands in the visible and middle IR regions (both afforded by the TM sensor design) can result in improved capabilities to accurately delineate land cover categories using a per point Gaussian maximum likelihood classifier. On the other hand, results indicate that the increase in spatial resolution to 30m does not significantly enhance classification accuracy. The spatial result points to an inherent limitation of a per point classifier and to the need to improve data analysis techniques to handle high spatial resolution data.

Williams, D. L.↗

Impact of thematic mapper sensor characteristics on classification accuracy

A three factor (spectral, spatial, and radiometric resolution), two level (TM and MSS) analysis of variance (ANOVA) approach allowed evaluation of the effects of each factor individually and in all possible combinations. Digital classification accuracy was used as the figure of merit. Nine study sites in Washington, DC, each of approximately 256 x 256 TM pixels, were randomly selected from the full scene for analysis. These results strongly suggest that the quantization level improvements and the addition of new spectral bands in the visible and middle IR regions (both afforded by the TM sensor design) can result in improved capabilities to accurately delineate land cover categories using a per point Gaussian maximum likelihood classifier. On the other hand, results indicate that the increase in spatial resolution to 30 m does not significantly enhance classification accuracy. The spatial result points to an inherent limitation of a per point classifier and to the need to improve data analysis techniques to handle high spatial resolution data.

Williams, D. L.↗

Dynamic Modeling Accuracy Dependence on Errors in Sensor Measurements, Mass Properties, and Aircraft Geometry

A nonlinear simulation of the NASA Generic Transport Model was used to investigate the effects of errors in sensor measurements, mass properties, and aircraft geometry on the accuracy of dynamic models identified from flight data. Measurements from a typical system identification maneuver were systematically and progressively deteriorated and then used to estimate stability and control derivatives within a Monte Carlo analysis. Based on the results, recommendations were provided for maximum allowable errors in sensor measurements, mass properties, and aircraft geometry to achieve desired levels of dynamic modeling accuracy. Results using other flight conditions, parameter estimation methods, and a full-scale F-16 nonlinear aircraft simulation were compared with these recommendations.

Grauer, Jared A.↗

Got an Attitude Problem?

Through a Small Business Innovation Research grant from NASA's Goddard Space Flight Center, Servo Corporation of America, Inc. built its Mini-Dual Sensor to provide attitude control for Earth-orbiting unmanned satellites. The sensor is an Earth horizon sensor that provides higher accuracy through the use of pyroelectric arrays and a patented radiance compensation scheme.This sensor gathers data with two pairs of lithium tantalate pyroelectric arrays that are positioned 90 degrees apart in the imaging plane. The Mini-Dual Earth Sensor is a high-accuracy sensor that could be used for attitude determination in future space missions.

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