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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Coherent Uncertainty Analysis of Aerosol Measurements from Multiple Satellite Sensors

Aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS altogether, a total of 11 different aerosol products were comparatively analyzed using data collocated with ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations within the Multi-sensor Aerosol Products Sampling System (MAPSS, http://giovanni.gsfc.nasa.gov/mapss/ and http://giovanni.gsfc.nasa.gov/aerostat/). The analysis was performed by comparing quality-screened satellite aerosol optical depth or thickness (AOD or AOT) retrievals during 2006-2010 to available collocated AERONET measurements globally, regionally, and seasonally, and deriving a number of statistical measures of accuracy. We used a robust statistical approach to detect and remove possible outliers in the collocated data that can bias the results of the analysis. Overall, the proportion of outliers in each of the quality-screened AOD products was within 12%. Squared correlation coefficient (R2) values of the satellite AOD retrievals relative to AERONET exceeded 0.6, with R2 for most of the products exceeding 0.7 over land and 0.8 over ocean. Root mean square error (RMSE) values for most of the AOD products were within 0.15 over land and 0.09 over ocean. We have been able to generate global maps showing regions where the different products present advantages over the others, as well as the relative performance of each product over different landcover types. It was observed that while MODIS, MISR, and SeaWiFS provide accurate retrievals over most of the landcover types, multi-angle capabilities make MISR the only sensor to retrieve reliable AOD over barren and snow / ice surfaces. Likewise, active sensing enables CALIOP to retrieve aerosol properties over bright-surface shrublands more accurately than the other sensors, while POLDER, which is the only one of the sensors capable of measuring polarized aerosols, outperforms other sensors in certain smoke-dominated regions, including broadleaf evergreens in Brazil and South-East Asia.

remote sensing↗
NASA NTRS2015

DRAGONS-A Micrometeoroid and Orbital Debris Impact Sensor on the ISS

The Debris Resistive/Acoustic Grid Orbital Navy-NASA Sensor (DRAGONS) is intended to be a large area impact sensor for in situ measurements of micrometeoroids and orbital debris (MMOD) in the sub-millimeter to millimeter size regime in the near Earth space environment. These MMOD particles are too small to be detected by ground-based radars and optical telescopes, but still large enough to be a serious threat to human space activities and robotic missions in the low Earth orbit (LEO) region. The nominal detection area of DRAGONS is 1 sq m, consisting of four 0.5 m × 0.5 m independent panels, but the dimensions of the panels can easily be modified to accommodate different payload constraints. The approach of the DRAGONS design is to combine three particle impact detection concepts to maximize information that can be extracted from each detected impact. The first is a resistive grid consisting of 75-micrometer-wide resistive lines, coated in parallel and separated by 75 micrometer gaps on a 25-micrometer thin film. When a particle a few hundred micrometers or larger strikes the grid, it would penetrate the film and sever some resistive lines. The size of the damage area can be estimated from the increased resistance. The second concept is based on polyvinylidene fluoride (PVDF) acoustic impact sensors. Multiple PVDF sensors are attached to the thin film to provide the impact timing information. From the different signal arrival times at different acoustic sensors, the impact location can be calculated via triangulation algorithms. The third concept employs a dual-layer film system where a second 25-micrometer film is placed 15 cm behind the resistive-grid film. Multiple PVDF acoustic sensors are also attached to the second film. The combination of impact timing and location information from the two films allows for direct measurements of the impact direction and speed. The DRAGONS technology development has been funded by several NASA organizations since 2002, first by the NASA Science Mission Directorate and the NASA Exploration Systems Mission Directorate, then by the NASA JSC Innovative Research and Development Program and the NASA Orbital Debris Program Office. The NASA Orbital Debris Program Office leads the effort with collaboration from the U.S. Naval Academy, Naval Research Laboratory, University of Kent at Canterbury in Great Britain, and Virginia Tech. The project recently reached a major milestone when DRAGONS was approved for a technology demonstration mission by the International Space Station (ISS) Program in October 2014. The plan is to deploy a 1 sq m DRAGONS on the ISS with the detection surface facing the ram-direction for 2 to 3 years. The tentative launch schedule is in early 2017. This mission will collect data on orbital debris in the sub-millimeter size regime to better define the small orbital debris environment at the ISS altitude. The mission will also advance the DRAGONS Technology Readiness Level to 9 and greatly enhance the opportunities to deploy DRAGONS on other spacecraft to high LEO orbits in the future.

Liou, J.-C.↗
NASA NTRS2014

Lightning Current Measurement with Fiber-Optic Sensor

A fiber-optic current sensor is successfully developed with many potential applications for electric current measurement. Originally developed for in-flight lightning measurement, the sensor utilizes Faraday Effect in an optical fiber. The Faraday Effect causes linear light polarization in a fiber to rotate when the fiber is exposed to a magnetic field. The polarization change is detected using a reflective polarimetric scheme. Forming fiber loops and applying Ampere's law, measuring the total light rotation results in the determination of the total current enclosed. The sensor is conformable to complex structure geometry. It is also non-conductive and immune to electromagnetic interference, saturation or hysteresis. Installation is non-intrusive, and the sensor can be safely routed through flammable areas. Two similar sensor systems are described in this paper. The first system operates at 1310nm laser wavelength and is capable of measuring approximately 300 A - 300 kA, a 60 dB range. Laboratory validation results of aircraft lighting direct and in-direct effect current amplitudes are reported for this sensor. The second system operates at 1550nm wavelength and can measure about 400 A - 400 kA. Triggered-lightning measurement data are presented for this system. Good results are achieved in all cases.

Nguyen, Truong X.↗
NASA NTRS2014

Infrared Spectral Radiance Intercomparisons With Satellite and Aircraft Sensors

Measurement system validation is critical for advanced satellite sounders to reach their full potential of improving observations of the Earth's atmosphere, clouds, and surface for enabling enhancements in weather prediction, climate monitoring capability, and environmental change detection. Experimental field campaigns, focusing on satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft, are an essential part of the validation task. Airborne FTS systems can enable an independent, SI-traceable measurement system validation by directly measuring the same level-1 parameters spatially and temporally coincident with the satellite sensor of interest. Continuation of aircraft under-flights for multiple satellites during multiple field campaigns enables long-term monitoring of system performance and inter-satellite cross-validation. The NASA / NPOESS Airborne Sounder Testbed - Interferometer (NAST-I) has been a significant contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This presentation gives an overview of benefits achieved using airborne sensors such as NAST-I utilizing examples from recent field campaigns. The methodology implemented is not only beneficial to new sensors such as the Cross-track Infrared Sounder (CrIS) flying aboard the Suomi NPP and future JPSS satellites but also of significant benefit to sensors of longer flight heritage such as the Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) on the AQUA and METOP-A platforms, respectively, to ensure data quality continuity important for climate and other applications. Infrared spectral radiance inter-comparisons are discussed with a particular focus on usage of NAST-I data for enabling inter-platform cross-validation.

Larar, Allen M.↗
NASA NTRS2013

Faster Array Training and Rapid Analysis for a Sensor Array Intended for an Event Monitor in Air

Environmental monitoring, in particular, air monitoring, is a critical need for human space flight. Both monitoring and life support systems have needs for closed loop process feedback and quality control for environmental factors. Monitoring protects the air environment and water supply for the astronaut crew and different sensors help ensure that the habitat falls within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the farther the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. There is an acknowledged need for an event monitor which samples the air continuously and provides near real-time information on changes in the air. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. We are working on a sensor array and new algorithms that will incorporate transient sensor responses in the analysis. Preliminary work has already showed more rapid quantification and identification of analytes and the potential for faster training time of the array. We will look at some of the factors that contribute to demonstrating faster training time for the array. Faster training will decrease the integrated sensor exposure to training analytes, which will also help extend sensor lifetime.

sensing array↗
NASA NTRS2015

Evaluation of MEMS-Based Wireless Accelerometer Sensors in Detecting Gear Tooth Faults in Helicopter Transmissions

The diagnostics capability of micro-electro-mechanical systems (MEMS) based rotating accelerometer sensors in detecting gear tooth crack failures in helicopter main-rotor transmissions was evaluated. MEMS sensors were installed on a pre-notched OH-58C spiral-bevel pinion gear. Endurance tests were performed and the gear was run to tooth fracture failure. Results from the MEMS sensor were compared to conventional accelerometers mounted on the transmission housing. Most of the four stationary accelerometers mounted on the gear box housing and most of the CI's used gave indications of failure at the end of the test. The MEMS system performed well and lasted the entire test. All MEMS accelerometers gave an indication of failure at the end of the test. The MEMS systems performed as well, if not better, than the stationary accelerometers mounted on the gear box housing with regards to gear tooth fault detection. For both the MEMS sensors and stationary sensors, the fault detection time was not much sooner than the actual tooth fracture time. The MEMS sensor spectrum data showed large first order shaft frequency sidebands due to the measurement rotating frame of reference. The method of constructing a pseudo tach signal from periodic characteristics of the vibration data was successful in deriving a TSA signal without an actual tach and proved as an effective way to improve fault detection for the MEMS.

gears↗
NASA NTRS2014

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earth's Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulationmethods to determinemission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit.

radiometry↗
NASA NTRS2013

In-Situ Transfer Standard and Coincident-View Intercomparisons for Sensor Cross-Calibration

There exist numerous methods for accomplishing on-orbit calibration. Methods include the reflectance-based approach relying on measurements of surface and atmospheric properties at the time of a sensor overpass as well as invariant scene approaches relying on knowledge of the temporal characteristics of the site. The current work examines typical cross-calibration methods and discusses the expected uncertainties of the methods. Data from the Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), Moderate Resolution Imaging Spectroradiometer (MODIS), and Thematic Mapper (TM) are used to demonstrate the limits of relative sensor-to-sensor calibration as applied to current sensors while Landsat-5 TM and Landsat-7 ETM+ are used to evaluate the limits of in situ site characterizations for SI-traceable cross calibration. The current work examines the difficulties in trending of results from cross-calibration approaches taking into account sampling issues, site-to-site variability, and accuracy of the method. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The results show that cross calibrations with absolute uncertainties lesser than 1.5 percent (1 sigma) are currently achievable even for sensors without coincident views.

Advanced Spaceborne Thermal Emission and Reflectio↗
NASA NTRS2014

Cross-Calibration of Earth Observing System Terra Satellite Sensors MODIS and ASTER

The Advanced Spaceborne Thermal Emissive and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) are two of the five sensors onboard the Earth Observing System's Terra satellite. These sensors share many similar spectral channels while having much different spatial and operational parameters. ASTER is a tasked sensor and sometimes referred to a zoom camera of the MODIS that collects a full-earth image every one to two days. It is important that these sensors have a consistent characterization and calibration for continued development and use of their data products. This work uses a variety of test sites to retrieve and validate intercalibration results. The refined calibration of Collection 6 of the Terra MODIS data set is leveraged to provide the up-to-date reference for trending and validation of ASTER. Special attention is given to spatially matching radiance measurements using prelaunch spatial response characterization of MODIS. Despite differences in spectral band properties and spatial scales, ASTER-MODIS is an ideal case for intercomparison since the sensors have nearly identical views and acquisitions times and therefore can be used as a baseline of intercalibration performance of other satellite sensor pairs.

MODIS↗
NASA NTRS2016

A Piezoelectric Shear Stress Sensor

In this paper, a piezoelectric sensor with a floating element was developed for shear stress measurement. The piezoelectric sensor was designed to detect the pure shear stress suppressing effects of normal stress generated from the vortex lift-up by applying opposite poling vectors to the: piezoelectric elements. The sensor was first calibrated in the lab by applying shear forces and it showed high sensitivity to shear stress (=91.3 +/- 2.1 pC/Pa) due to the high piezoelectric coefficients of PMN-33%PT (d31=-1330 pC/N). The sensor also showed almost no sensitivity to normal stress (less than 1.2 pC/Pa) because of the electromechanical symmetry of the device. The usable frequency range of the sensor is 0-800 Hz. Keywords: Piezoelectric sensor, shear stress, floating element, electromechanical symmetry

Kim, Taeyang↗
NASA NTRS2017

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level precision at a range of two meters with a 1U target.

Carter, C.↗
NASA NTRS2017

Robust Targeting for the Smartphone Video Guidance Sensor

The Smartphone Video Guidance Sensor (SVGS) is a miniature, self-contained autonomous rendezvous and docking sensor developed using a commercial off the shelf Android-based smartphone. It aims to provide a miniaturized solution for rendezvous and docking, enabling small satellites to conduct proximity operations and formation flying while minimizing interference with a primary payload. Previously, the sensor was limited by a slow (2 Hz) refresh rate and its use of retro-reflectors, both of which contributed to a limited operating environment. To advance the technology readiness level, a modified approach was developed, combining a multi-colored LED target with a focused target-detection algorithm. Alone, the use of an LED system was determined to be much more reliable, though slower, than the retro-reflector system. The focused target-detection system was developed in response to this problem to mitigate the speed reduction of using color. However, it also improved the reliability. In combination these two methods have been demonstrated to dramatically increase sensor speed and allow the sensor to select the target even with significant noise interfering with the sensor, providing millimeter level accuracy at a range of two meters with a 1U target.

Carter, Christopher↗
NASA NTRS2017

A Piezoelectric Passive Wireless Sensor for Monitoring Strain

Interest in passive wireless sensing has grown over the past few decades to meet demands in structural health monitoring.(Deivasigamani et al., 2013; Wilson and Juarez, 2014) This work describes a passive wireless sensor for monitoring strain, which does not have an embedded battery or chip. Without an embedded battery, the passive wireless sensor has the potential to maintain its functionality over long periods in remote/harsh environments. This work also focuses on monitoring small strain (less than 1000 micro-ɛ). The wireless sensing system includes a reader unit, a coil-like transponder, and a sensing unit. It operates in the Megahertz (MHz) frequency range, which allows for a few centimeters of separation between the reader and sensing unit during measurements. The sensing unit is a strain-sensitive piezoelectric resonator that maximizes the energy efficiency at the resonance frequency, so it converts nanoscale mechanical variations to detectable differences in electrical signal. In response to an external loading, the piezoelectric sensor breaks from its original electromechanical equilibrium, and the resonant frequency shifts as the system reaches a new balanced equilibrium. In this work, the fixture of the sensing unit is a small, sticker-like package that converts the surface strain of a test material to measurable shifts in resonant frequencies. Furthermore, electromechanical modeling provides a lumped-parameter model of the system to describe and predict the measured wireless signals of the sensor. Detailed characterization demonstrates how this wireless sensor has resolution comparable to that of conventional wired strain sensors for monitoring small strain.

Zou, Xiyue↗
NASA NTRS2018

Sensor Integrated Pilot Mask for On-Board, Real-Time, Monitoring of Pilot Breathing Gas

A pilot's job is unique in the demands it places on the human body, and many conditions can seriously affect pilot performance, threatening mission completion and pilot safety. The gas in a flight mask contains key indicators of the pilot's physiological state, including oxygen inhaled and carbon dioxide exhaled, which can signal hypoxia, hyperoxia, hypocapnia, and hypercapnia. A fiber optic-based sensor system, integrated into the pilot mask, has been developed to monitor in real time, during flight, the pilot breathing gas levels. Monitoring the partial pressure of oxygen and carbon dioxide in the pilot mask supports real-time closed loop control of the on-board oxygen generation system, based on a direct reading of what the pilot is actually breathing. The pilot Mask Sensor (MASES) system incorporates luminescence sensors for pO2, pCO2, relative humidity, pressure, and temperature in a compact probe in the pilot mask; it is based on sensor technology developed for gas monitoring in space suit systems, in work supported by NASA under the Small Business Innovation Research program. Relevant requirements for the MASES system include sensor operation while wet, operation at reduced pressure, ability to withstand rapid decompression, operation in a pure oxygen atmosphere, low power consumption, a compact readout unit, and flexible miniature sensors; many of these requirements are shared with gas monitors in space suits. Data are presented from tests conducted with human subjects in an altitude chamber and in a centrifuge.

Delgado Alonso, Jesus↗
NASA NTRS2018

Enabling Experimental Evolution: Multi-Parameter Sensor System Integration into a Culture/Stressor Biofluidics System

Experimental evolution (EE) exposes microbial communities to ecological stressors, simulating dynamics up to near-extinction events. Combined with comparative sequencing and other molecular tools, such data can inform the genetic and other biological mechanisms underlying extremophile adaptation, and other observed effects. Automating this type of experiment using biofluidics can mitigate many traditional obstacles, including delays in assay results and environment adjustment and the need for many replicates. A first-generation device for automating EE procedures, the Automated Adaptive Directed Evolution Chamber (AADEC), was developed at NASA Ames. UV-C radiation was the stressor, an LED-photodiode array measured optical density, magnetic agitation and peristaltic pump systems ensured nutrient availability, and Arduino microcontrollers provided control. Escherichia coli in LB kanamycin media was used for testing and performance verification. A manual laboratory procedure with timed exposure to UV-C was performed to typify tolerance acquisition. Approximately a 106 factor increase in survival ratio was recorded over multiple iterations. Currently, a second-generation device is being developed integrating more real-time sensors: redox potential (ORP), indicating available/consumed metabolic energy; dissolved oxygen (DO), indicating aerobic/anaerobic growth; pH, indicating metabolic products; and electrical conductivity (EC), another indicator of metabolic products. The EC sensor system was constructed and calibrated in-house and matched commercial sensors in the required range. A Raspberry Pi computer automated the electrical system, allowing real-time data acquisition. The fluidics card was made of CNC-milled polycarbonate for biocompatibility. Each sensor parameter can also be used as a selection pressure alone or in combination with others to create extreme microbial environments. As a proof of concept, this work demonstrated sensor operation in one pair of growth-sensor chambers. It can be expanded to a multi-chamber system to enable inter-culture comparisons and multi-population studies. The prior Arduino system will be ported to the RPi system. Future stressors to be added include thermal, reactive oxygen species, and varying nutrient availability.

Govinda Raj, Chinmayee↗
NASA NTRS2014

Diagnosability-Based Sensor Placement through Structural Model Decomposition

Systems health management, and in particular fault diagnosis, is important for ensuring safe, correct, and efficient operation of complex engineering systems. The performance of an online health monitoring system depends critically on the available sensors of the system. However, the set of selected sensors is subject to many constraints, such as cost and weight, and hence, these sensors must be selected judiciously. This paper presents an offline design-time sensor placement approach for complex systems. Our diagnosis method is built upon the analysis of model-based residuals, which are computed using structural model decomposition. Sensor placement in this framework manifests as a residual selection problem, and we aim to find the set of residuals that achieves single-fault diagnosability of the system, uses the minimum number of sensors, and corresponds to the best model decomposition for the best distribution of the diagnosis system. We present a set of algorithms for solving this problem and compare their performance in terms of computational complexity and optimality of solutions. We demonstrate the approach using a benchmark multi-tank system.

Daigle, Matthew↗
NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗
NASA NTRS2019

Analytic Spacecraft Attitude and Rate Estimation Performance During Attitude Sensor Outages

Analytic expressions for spacecraft attitude and rate estimation performance of an attitude estimation filter in terms of sensor specifications are useful tools for spacecraft design. Farrenkopf (1978) famously found analytic expressions for steady-state pre-update and post-update attitude and gyro bias estimate error variances for an attitude estimation filter for a single-axis spacecraft with a Rate Output Gyro (ROG). Markley and Reynolds (2000) extended the analysis for a Rate-Integrating Gyro (RIG) with angle white noise. These expressions allow for the rapid evaluation of system performance during preliminary mission design phases. One contribution of this paper is the analytic calculation of the steady-state pre-update and post-update angular rate estimate uncertainty for both the ROG and RIG cases. The primary contribution of this paper is the extension of the results for both the ROG and the RIG cases to the situation of an attitude sensor outage. This situation arises frequently in practice; for example when a star sensor’s field of view is occluded, when a star sensor’s readings are unreliable during a thruster burn that vibrates the spacecraft, or during star sensor outages due to radiation upsets. Analytic expressions for the attitude estimate uncertainty, gyro bias estimate uncertainty, and angular rate estimate uncertainty are given in terms of the attitude sensor outage interval, the star tracker measurement noise, and gyro noise parameters. Validity of the analytic results is demonstrated via Monte Carlo simulation.

Galante, Joseph M.↗