Results for “detection” — Page 15

NASA NTRS2005

Multiple-Bit Differential Detection of OQPSK

A multiple-bit differential-detection method has been proposed for the reception of radio signals modulated with offset quadrature phase-shift keying (offset QPSK or OQPSK). The method is also applicable to other spectrally efficient offset quadrature modulations. This method is based partly on the same principles as those of a multiple-symbol differential-detection method for M-ary QPSK, which includes QPSK (that is, non-offset QPSK) as a special case. That method was introduced more than a decade ago by the author of the present method as a means of improving performance relative to a traditional (two-symbol observation) differential-detection scheme. Instead of symbol-by-symbol detection, both that method and the present one are based on a concept of maximum-likelihood sequence estimation (MLSE). As applied to the modulations in question, MLSE involves consideration of (1) all possible binary data sequences that could have been received during an observation time of some number, N, of symbol periods and (2) selection of the sequence that yields the best match to the noise-corrupted signal received during that time. The performance of the prior method was shown to range from that of traditional differential detection for short observation times (small N) to that of ideal coherent detection (with differential encoding) for long observation times (large N).

Simon, Marvin↗

NASA NTRS2012

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

Brennan, Shane↗

NASA NTRS2012

Water Detection Based on Color Variation

This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

Rankin, Arturo L.↗

NASA NTRS2012

Detecting Methane From Leaking Pipelines and as Greenhouse Gas in the Atmosphere

Laser remote sensing measurements of trace gases from orbit can provide unprecedented information about important planetary science and answer critical questions about planetary atmospheres. Methane (CH4) is the second most important anthropogenically produced greenhouse gas. Though its atmospheric abundance is much less than that of CO2 (1.78 ppm vs. 380 ppm), it has much larger greenhouse heating potential. CH4 also contributes to pollution in the lower atmosphere through chemical reactions, leading to ozone production. Atmospheric CH4 concentrations have been increasing as a result of increased fossil fuel production, rice farming, livestock, and landfills. Natural sources of CH4 include wetlands, wild fires, and termites, and perhaps other unknown sources. Important sinks for CH4 include non-saturated soils and oxidation by hydroxyl radicals in the atmosphere. Remotely measuring CH4 and other biogenic molecules (such as ethane and formaldehyde) on Mars also has important implications on the existence of life on Mars. Measuring CH4 at very low (ppb) concentrations from orbit will dramatically improve the sensitivity and spatial resolution in the search for CH4 vents and sub-surface life on other planets. A capability has been developed using lasers and spectroscopic detection techniques for the remote measurements of trace gases in open paths. Detection of CH4, CO2, H2O, and CO in absorption cells and in open paths, both in the mid- IR and near-IR region, has been demonstrated using an Optical Parametric Amplifier laser transmitter developed at GSFC. With this transmitter, it would be possible to develop a remote sensing methane instrument. CH4 detection also has very important commercial applications. Pipeline leak detection from an aircraft or a helicopter can significantly reduce cost, response time, and pinpoint the location. The main advantage is the ability to rapidly detect CH4 leaks remotely. This is extremely important for the petrochemical industry. This capability can be used in manned or unmanned airborne platforms for the detection of leaks in pipelines and other areas of interest where a CH4 leak is suspected.

Riris, Haris↗

NASA NTRS2012

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Yost, Christopher R.↗

NASA NTRS2011

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Whiteman, David N.↗

NASA NTRS2013

Semi-Supervised Eigenbasis Novelty Detection

Recent discoveries in high-time-resolution radio astronomy data have focused attention on a new class of events. Fast transients are rare pulses of radio frequency energy lasting from microseconds to seconds that might be produced by a variety of exotic astrophysical phenomena. For example, X-ray bursts, neutron stars, and active galactic nuclei are all possible sources of short-duration, transient radio signals. It is difficult to anticipate where such signals might appear, and they are most commonly discovered through analysis of high-time- resolution data that had been collected for other purposes. Transients are often faint and difficult to detect, so improved detection algorithms can directly benefit the science yield of all such commensal monitoring. A new detection algorithm learns a low-dimensional linear manifold for describing the normal data. High reconstruction error indicates a novel signal that does not match the patterns of normal data. One unsupervised portion of the manifold model adapts its representation in response to recent data. A second supervised portion of the model is made of a basis trained in advance using labeled examples of RFI; this prevents false positives due to these events. For a linear model, an orthonormalization operation is used to combine these bases prior to the anomaly detection decision. Another novel aspect of the approach lies in combining basis vectors learned in an unsupervised, online fashion from the data stream with supervised basis vectors learned in advance from known examples of false alarms. Adaptive, data-driven detection is achieved that is also informed by existing domain knowledge about signals that may be statistically anomalous, but are not interesting and should therefore be ignored. The method was evaluated using data from the Parkes Multibeam Survey. This data set was originally collected to search for pulsars, which are astronomical sources that emit radio pulses at regular periods. However, several non-pulsar anomalies have recently been discovered in this dataset, making it a compelling test case. By explicitly filtering known false alarm patterns, the approach yields significantly better performance than current transient detection methods.

Wagstaff, Kiri L.↗

NASA NTRS2013

ISS Ammonia Leak Detection Through X-Ray Fluorescence

Ammonia leaks are a significant concern for the International Space Station (ISS). The ISS has external transport lines that direct liquid ammonia to radiator panels where the ammonia is cooled and then brought back to thermal control units. These transport lines and radiator panels are subject to stress from micrometeorites and temperature variations, and have developed small leaks. The ISS can accommodate these leaks at their present rate, but if the rate increased by a factor of ten, it could potentially deplete the ammonia supply and impact the proper functioning of the ISS thermal control system, causing a serious safety risk. A proposed ISS astrophysics instrument, the Lobster X-Ray Monitor, can be used to detect and localize ISS ammonia leaks. Based on the optical design of the eye of its namesake crustacean, the Lobster detector gives simultaneously large field of view and good position resolution. The leak detection principle is that the nitrogen in the leaking ammonia will be ionized by X-rays from the Sun, and then emit its own characteristic Xray signal. The Lobster instrument, nominally facing zenith for its astrophysics observations, can be periodically pointed towards the ISS radiator panels and some sections of the transport lines to detect and localize the characteristic X-rays from the ammonia leaks. Another possibility is to use the ISS robot arm to grab the Lobster instrument and scan it across the transport lines and radiator panels. In this case the leak detection can be made more sensitive by including a focused 100-microampere electron beam to stimulate X-ray emission from the leaking nitrogen. Laboratory studies have shown that either approach can be used to locate ammonia leaks at the level of 0.1 kg/day, a threshold rate of concern for the ISS. The Lobster instrument uses two main components: (1) a microchannel plate optic (also known as a Lobster optic) that focuses the X-rays and directs them to the focal plane, and (2) a CCD (charge coupled device) focal plane detector that reads out the position and energy of the X-rays, allowing a determination of the leak location. The effective area of the detection system is approximately 2 cm(exp2) at 1 keV. The Lobster astrophysics instrument, designed for monitoring the sky for Xray transients, gives high sensitivity along with large field of view (30×30deg) and good spatial resolution (1 arc min). This offers a significant benefit for detecting ISS ammonia leaks, since the goal is to localize small leaks as efficiently as possible.

Camp, Jordan↗

NASA NTRS2013

Detection and Quantification of Nitrogen Compounds in Martian Solid Samples by the Sample Analysis at Mars (SAM) Instrument Suite

The Sample Analysis at Mars (SAM) instrument suite on the Mars Science Laboratory (MSL) Curiosity Rover detected both reduced and oxidized nitrogen-bearing compounds during the pyrolysis of surface materials from three sites at Gale Crater. Preliminary detections of nitrogen species include NO, HCN, ClCN, CH3CN, and TFMA (trifluoro-Nmethyl-acetamide). On Earth, nitrogen is a crucial bio-element, and nitrogen availability controls productivity in many environments. Nitrogen has also recently been detected in the form of CN in inclusions in the Martian meteorite Tissint, and isotopically heavy nitrogen (delta N-15 approx +100per mille) has been measured during stepped combustion experiments in several SNC meteorites. The detection of nitrogen-bearing compounds in Martian regolith would have important implications for the habitability of ancient Mars. However, confirmation of indigenous Martian nitrogen bearing compounds will require ruling out their formation from the terrestrial derivatization reagents (e.g. N-methyl-N-tert-butyldimethylsilyl-trifluoroacetamide, MTBSTFA and dimethylformamide, DMF) carried for SAM's wet chemistry experiment that contribute to the SAM background. The nitrogen species we detect in the SAM solid sample analyses can also be produced during laboratory pyrolysis experiments where these reagents are heated in the presence of perchlorate, a compound that has also been identified by SAM in Mars solid samples. However, this does not preclude a Martian origin for some of these compounds, which are present in nanomolar concentrations in SAM evolved gas analyses. Analysis of SAM data and laboratory breadboard tests are underway to determine whether nitrogen species are present at higher concentrations than can be accounted for by maximum estimates of nitrogen contribution from MTBSTFA and DMF. In addition, methods are currently being developed to use GC Column 6, (functionally similar to a commercial Q-Bond column), to separate and identify unretained compounds such as NO, N2O, and NO2, which are difficult to detect by EGA-MS due to mass interferences at 30, 44 and 46, respectively. Here we present evolved gas analysis-mass spectrometry (EGA-MS) and gas chromatography mass spectrometry (GC-MS) data on the identification and quantification of these nitrogen-bearing compounds, and suggestions for their origins

Stern, Jennifer C.↗

NASA NTRS2015

Investigation of Asymmetric Thrust Detection with Demonstration in a Real-Time Simulation Testbed

The purpose of this effort is to develop, demonstrate, and evaluate three asymmetric thrust detection approaches to aid in the reduction of asymmetric thrust-induced aviation accidents. This paper presents the results from that effort and their evaluation in simulation studies, including those from a real-time flight simulation testbed. Asymmetric thrust is recognized as a contributing factor in several Propulsion System Malfunction plus Inappropriate Crew Response (PSM+ICR) aviation accidents. As an improvement over the state-of-the-art, providing annunciation of asymmetric thrust to alert the crew may hold safety benefits. For this, the reliable detection and confirmation of asymmetric thrust conditions is required. For this work, three asymmetric thrust detection methods are presented along with their results obtained through simulation studies. Representative asymmetric thrust conditions are modeled in simulation based on failure scenarios similar to those reported in aviation incident and accident descriptions. These simulated asymmetric thrust scenarios, combined with actual aircraft operational flight data, are then used to conduct a sensitivity study regarding the detection capabilities of the three methods. Additional evaluation results are presented based on pilot-in-the-loop simulation studies conducted in the NASA Glenn Research Center (GRC) flight simulation testbed. Data obtained from this flight simulation facility are used to further evaluate the effectiveness and accuracy of the asymmetric thrust detection approaches. Generally, the asymmetric thrust conditions are correctly detected and confirmed.

aircraft safety↗

NASA NTRS2015

Investigation of Asymmetric Thrust Detection with Demonstration in a Real-Time Simulation Testbed

The purpose of this effort is to develop, demonstrate, and evaluate three asymmetric thrust detection approaches to aid in the reduction of asymmetric thrust-induced aviation accidents. This paper presents the results from that effort and their evaluation in simulation studies, including those from a real-time flight simulation testbed. Asymmetric thrust is recognized as a contributing factor in several Propulsion System Malfunction plus Inappropriate Crew Response (PSM+ICR) aviation accidents. As an improvement over the state-of-the-art, providing annunciation of asymmetric thrust to alert the crew may hold safety benefits. For this, the reliable detection and confirmation of asymmetric thrust conditions is required. For this work, three asymmetric thrust detection methods are presented along with their results obtained through simulation studies. Representative asymmetric thrust conditions are modeled in simulation based on failure scenarios similar to those reported in aviation incident and accident descriptions. These simulated asymmetric thrust scenarios, combined with actual aircraft operational flight data, are then used to conduct a sensitivity study regarding the detection capabilities of the three methods. Additional evaluation results are presented based on pilot-in-the-loop simulation studies conducted in the NASA Glenn Research Center (GRC) flight simulation testbed. Data obtained from this flight simulation facility are used to further evaluate the effectiveness and accuracy of the asymmetric thrust detection approaches. Generally, the asymmetric thrust conditions are correctly detected and confirmed.

gas turbine engines↗

NASA NTRS2016

Investigation of Asymmetric Thrust Detection with Demonstration in a Real-Time Simulation Testbed

The purpose of this effort is to develop, demonstrate, and evaluate three asymmetric thrust detection approaches to aid in the reduction of asymmetric thrust-induced aviation accidents. This paper presents the results from that effort and their evaluation in simulation studies, including those from a real-time flight simulation testbed. Asymmetric thrust is recognized as a contributing factor in several Propulsion System Malfunction plus Inappropriate Crew Response (PSM+ICR) aviation accidents. As an improvement over the state-of-the-art, providing annunciation of asymmetric thrust to alert the crew may hold safety benefits. For this, the reliable detection and confirmation of asymmetric thrust conditions is required. For this work, three asymmetric thrust detection methods are presented along with their results obtained through simulation studies. Representative asymmetric thrust conditions are modeled in simulation based on failure scenarios similar to those reported in aviation incident and accident descriptions. These simulated asymmetric thrust scenarios, combined with actual aircraft operational flight data, are then used to conduct a sensitivity study regarding the detection capabilities of the three methods. Additional evaluation results are presented based on pilot-in-the-loop simulation studies conducted in the NASA Glenn Research Center (GRC) flight simulation testbed. Data obtained from this flight simulation facility are used to further evaluate the effectiveness and accuracy of the asymmetric thrust detection approaches. Generally, the asymmetric thrust conditions are correctly detected and confirmed.

propulsion system performance↗

NASA NTRS2016

Fire Detection Tradeoffs as a Function of Vehicle Parameters

Fire survivability depends on the detection of and response to a fire before it has produced an unacceptable environment in the vehicle. This detection time is the result of interplay between the fire burning and growth rates; the vehicle size; the detection system design; the transport time to the detector (controlled by the level of mixing in the vehicle); and the rate at which the life support system filters the atmosphere, potentially removing the detected species or particles. Given the large differences in critical vehicle parameters (volume, mixing rate and filtration rate) the detection approach that works for a large vehicle (e.g. the ISS) may not be the best choice for a smaller crew capsule. This paper examines the impact of vehicle size and environmental control and life support system parameters on the detectability of fires in comparison to the hazard they present. A lumped element model was developed that considers smoke, heat, and toxic product release rates in comparison to mixing and filtration rates in the vehicle. Recent work has quantified the production rate of smoke and several hazardous species from overheated spacecraft polymers. These results are used as the input data set in the lumped element model in combination with the transport behavior of major toxic products released by overheating spacecraft materials to evaluate the necessary alarm thresholds to enable appropriate response to the fire hazard.

microgravity↗

NASA NTRS2017

Reliably Detectable Flaw Size for NDE Methods that Use Calibration

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh1823 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

Koshti, Ajay M.↗

NASA NTRS2016

Fire Detection Tradeoffs as a Function of Vehicle Parameters

Fire survivability depends on the detection of and response to a fire before it has produced an unacceptable environment in the vehicle. This detection time is the result of interplay between the fire burning and growth rates; the vehicle size; the detection system design; the transport time to the detector (controlled by the level of mixing in the vehicle); and the rate at which the life support system filters the atmosphere, potentially removing the detected species or particles. Given the large differences in critical vehicle parameters (volume, mixing rate and filtration rate) the detection approach that works for a large vehicle (e.g. the ISS) may not be the best choice for a smaller crew capsule. This paper examines the impact of vehicle size and environmental control and life support system parameters on the detectability of fires in comparison to the hazard they present. A lumped element model was developed that considers smoke, heat, and toxic product release rates in comparison to mixing and filtration rates in the vehicle. Recent work has quantified the production rate of smoke and several hazardous species from overheated spacecraft polymers. These results are used as the input data set in the lumped element model in combination with the transport behavior of major toxic products released by overheating spacecraft materials to evaluate the necessary alarm thresholds to enable appropriate response to the fire hazard.

microgravity↗

NASA NTRS2017

Damage Detection Sensor System for Aerospace and Multiple Applications

The damage detection sensory system is an intelligent damage detection ‘skin’ that can be embedded into rigid or flexible structures, providing a lightweight capability for in-situ health monitoring for applications such as spacecraft, expandable or inflatable structures, extravehicular activities (EVA) suits, smart wearables, and other applications where diagnostic impact damage monitoring might be critical. The sensor systems can be customized for detecting location, damage size, and depth, with velocity options and can be designed for particular environments for monitoring of impact or physical damage to a structure. The operation of the sensor detection system is currently based on the use of parallel conductive traces placed on a firm or flexible surface. Several detection layers can be implemented, where alternate layers are arranged in orthogonal direction with respect to the adjacent layers allowing for location and depth calculations. Increased flexibility of the damage detection sensor system designs will also be introduced.

Williams, M.↗

NASA NTRS2017

System and Method for Multi-Wavelength Optical Signal Detection

The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

McGlone, Thomas D.↗

NASA NTRS2018

Exoplanet Detection Synenergy Between Gaia and the WFIRST Coronagraph

Future astrometric detections of exoplanets from the Gaia mission will augment and improve the sample of targets accessible to the Coronagraph Instrument (CGI) on WFIRST. We assessed the joint detection sensitivity of Gaia and WFIRST by modeling random planet populations around nearby (d less than 20 pc), bright (V less than 6) stars, and applying nominal detection thresholds for each mission. Our analysis suggests that only a small number of the new planet detections from Gaia will be favorable for spectroscopic characterization by WFIRST CGI: 1-3 planets, depending on the assumed planet population model. The target stars hosting gas giants detectable to both missions tend to be GK dwarfs with brightness between V = 3-5, and distances within 10 pc. While few in number, these new Gaia-detected exoplanets could be exceptionally valuable targets for WFIRST due to the ability to incorporate astrometric mass estimates into the spectral retrieval of atmospheric parameters.

Zimmerman, Neil T.↗