Low-cost real-time aerial object detection and GPS location tracking pipeline
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Allan Lago↗
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Results for “Object detection”
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Radar detectability of asteroids - A survey of opportunities for 1977 through 1987
The study of asteroids by earth-based radar during the period 1977 to 1987 is discussed. Detection modeling, including backscattering laws, limits of detectability, and in particular, measurement of center frequency, center-to-limb bandwidth, and areal spectral density, is reviewed. The number of detectable objects and detectable events falling into various 5-decibel radar target loss slots is estimated; a total of 60 different asteroids should be observable on about 130 occasions by either the Goldstone or Arecibo radar systems during the decade considered. Furthermore, the detectability margins for many objects should be large enough to permit more refined analysis of the radar spectrograms. Data acquired during the ten-year period may be used to find the radius, average surface roughness, rotation rate, direction of polar axis, and estimates of the Doppler frequency offsets for many of the asteroids. Also, information about radar albedos and orbital parameters may be obtainable in a number of cases.
Jurgens, R. F.↗
Extragalactic H 2 regions in the UV: Implications for primeval galaxies and quasars
Three extragalactic regions of rapid star formation with red shifts great enough to separate the L alpha region from geocoronal L alpha were observed with the IUE satellite. Only the low metal abundance object had detectable L alpha emission. L alpha is therefore expected to be weak or absent in collapsed primeval galaxies. The detected object has a L alpha H beta identical to that of quasars.
Meier, D. L.↗
Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control
This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.
Ahumada, Albert J., Jr.↗
Detection of Objects Hidden in Highly Scattering Media Using Time-Gated Imaging Methods
Non-intrusive and non-invasive optical imaging techniques has generated great interest among researchers for their potential applications to biological study, device characterization, surface defect detection, and jet fuel dynamics. Non-linear optical parametric amplification gate (NLOPG) has been used to detect back-scattered images of objects hidden in diluted Intralipid solutions. To directly detect objects hidden in highly scattering media, the diffusive component of light needs to be sorted out from early arrived ballistic and snake photons. In an optical imaging system, images are collected in transmission or back-scattered geometry. The early arrival photons in the transmission approach, always carry the direct information of the hidden object embedded in the turbid medium. In the back-scattered approach, the result is not so forth coming. In the presence of a scattering host, the first arrival photons in back-scattered approach will be directly photons from the host material. In the presentation, NLOPG was applied to acquire time resolved back-scattered images under the phase matching condition. A time-gated amplified signal was obtained through this NLOPG process. The system's gain was approximately 100 times. The time-gate was achieved through phase matching condition where only coherent photons retain their phase. As a result, the diffusive photons, which were the primary contributor to the background, were removed. With a large dynamic range and high resolution, time-gated early light imaging has the potential for improving rocket/aircraft design by determining jets shape and particle sizes. Refinements to these techniques may enable drop size measurements in the highly scattering, optically dense region of multi-element rocket injectors. These types of measurements should greatly enhance the design of stable, and higher performing rocket engines.
Galland, Pierre A.↗
Michigan Orbital DEbris Survey Telescope Observations of the Geosynchronous Orbital Debris Environment. Observing Years: 2007-2009
NASA uses the Michigan Orbital DEbris Survey Telescope (MODEST), the University of Michigan's 0.61-m aperture Curtis-Schmidt telescope at the Cerro Tololo Inter-American Observatory in Chile, to help characterize the debris environment in geosynchronous orbit; this began in February 2001 and continues to the present day. Detected objects that are found to be on the U.S. Space Surveillance Network cataloged objects list are termed correlated targets (CTs), while those not found on the list are called uncorrelated targets (UCTs). This Johnson Space Center report provides details of observational and data-reduction processes for the entire MODEST dataset acquired in calendar years (CYs) 2007, 2008, and 2009. Specifically, this report describes the collection and analysis of 36 nights of data collected in CY 2007, 43 nights of data collected in CY 2008, and 43 nights of data collected in CY 2009. MODEST is equipped with a 2048 x 2048-pixel charged coupled device camera with a 1.3 by 1.3 deg field of view. This system is capable of detecting objects fainter than 18th magnitude (R filter) using a 5-s integration. This corresponds to a 20-cm diameter, 0.175-albedo object at 36,000 km altitude assuming a diffuse Lambertian phase function. The average number of detections each night over all 3 years was 26. The percentage of this number that represented the UCT population ranged from 34% to 18%, depending on the observing strategy and the field center location. Due to the short orbital arc over which observations are made, the eccentricity of the object s orbit is extremely difficult to measure accurately. Therefore, a circular orbit was assumed when calculating the orbital elements. A comparison of the measured inclination (INC), right ascension of ascending node (RAAN), and mean motion to the quantities for CTs from the U.S. Space Surveillance Network shows acceptable errors. This analysis lends credibility to the determination of the UCT orbital distributions. Figure 1 shows the size distribution of 3,143 objects detected in the data processed for CYs 2007, 2008, and 2009. The actual peak of the absolute magnitude distribution for the functional correlated targets is 10th magnitude, whereas the peak was 11th magnitude in 2002 2003 and 10th magnitude for 2004-2006. An absolute magnitude of 10.5 corresponds to objects with average diameters of 6.3 m, assuming an albedo of 0.175 and a diffuse Lambertian phase function. This result generally agrees with the known sizes of intact satellites. The absolute magnitude distribution for the UCTs is broad, but starts to roll off near 25 cm diameter or 17.5 magnitude. This roll off in the distribution reflects the detection capability of MODEST, not the true nature of the population. The true population is believed to continue at the same slope through fainter magnitudes based on comparisons with the LEO break-up law.
Abercromby, K. J.↗
Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility
Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace (NAS). Since there are numerous more AAM and UAM aircraft than commercial aircraft, it will be challenging to utilize the same ATC/ATM architectures. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.
distributed sensing↗
Ground-Based Vision Tracker for Advanced Air Mobility and Urban Air Mobility
Advanced Air Mobility (AAM) Air Mobility and Urban Air Mobility (UAM) require aircraft surveillance and monitoring for safety and security. Persistent tracking of flying objects provides Air Traffic Control (ATC) and Air Traffic Management (ATM) continuous coverage and knowledge of the national airspace system (NAS). Given the significant disparity in the number of AAM and UAM aircraft compared to commercial aircraft in the NAS, coupled with the dense AAM/UAM operations in urban environments, employing the existing ATC/ATM architectures poses considerable challenges. A first step in creating a similar ATC/ATM architecture for AAM/UAM will require ground-based and airborne-based sensors to provide monitoring, which will be difficult in urban environments due to GPS degradation. This paper proposes a vision-based tracking method with static cameras by utilizing image subtraction and blob detection, which avoids adding additional electromagnetic interferences in the environment with sensors such as radar. The ground-based vision tracker (GBVT) outputs the detected objects' azimuth and elevation angles from unmanned aerial system (UAS) flight tests. Future and ongoing work includes sending the detected objects' azimuth and elevation angles as inputs for an extended Kalman filter (EKF) to estimate the position and velocity of the detected object.
distributed sensing↗
Algorithms for detection of objects in image sequences captured from an airborne imaging system
This research was initiated as a part of the effort at the NASA Ames Research Center to design a computer vision based system that can enhance the safety of navigation by aiding the pilots in detecting various obstacles on the runway during critical section of the flight such as a landing maneuver. The primary goal is the development of algorithms for detection of moving objects from a sequence of images obtained from an on-board video camera. Image regions corresponding to the independently moving objects are segmented from the background by applying constraint filtering on the optical flow computed from the initial few frames of the sequence. These detected regions are tracked over subsequent frames using a model based tracking algorithm. Position and velocity of the moving objects in the world coordinate is estimated using an extended Kalman filter. The algorithms are tested using the NASA line image sequence with six static trucks and a simulated moving truck and experimental results are described. Various limitations of the currently implemented version of the above algorithm are identified and possible solutions to build a practical working system are investigated.
Kasturi, Rangachar↗
Ultraviolet Galaxy Counts From STIS Observations of The Hubble Deep Fields
We present galaxy counts in the near and far ultraviolet (NUV and FUV) obtained from Space Telescope Imaging Spectrograph (STIS) observations of portions of the Hubble Deep Field North, (HDFN), the Hubble Deep Field South, (HDFS) and a parallel field near the HDFN. All three fields have deep (AB>29) optical imaging, and we determine magnitudes by taking the ultraviolet flux detected within the limiting optical isophote. An analysis of the UV-optical colors of detected objects, combined with a visual inspection of the UV images, indicates that there are no detectable objects in the UV images which are not also detected in the optical. We measure the detection area and completeness as a function of magnitude by taking the size-magnitude distribution of galaxies in the entire HDFN WFPC2 V+I image, applying the measured UV-optical colors from the detected galaxies, and determining the total area over which each galaxy would have been detected in the UV images. The average area for the simulated galaxies in each UV magnitude bin, (including galaxies which would not be detected at all), provides the effective area and completeness for the bin. We test this procedure with Monte Carlo simulations. The galaxy counts reach to AB=29 in both the NUV and FUV; 1 magnitude fainter than the HDF F30OW counts, and 7 magnitudes fainter than balloon-based counts. We compare our measured counts to various models.
Gardner, J. P.↗
Optimal addition of images for detection and photometry
In this paper we describe weighting techniques used for the optimal coaddition of charge coupled devices (CCD) frames with differing characteristics. Optimal means maximum signal to noise (S/N) for stellar objects. We derive formulas for four applications: (1) object detection via matched filter, (2) object detection identical to DAOFIND, (3) aperture photometry, and (4) ALLSTAR profile-fitting photometry. We have included examples involving 21 frames for which either the sky brightness or image resolution varied by a factor of 3. The gains in S/N were modest for most of the examples, except for DAOFIND detection with varying image resolution which exhibited a substantial S/N increase. Even though the only consideration was maximizing S/N, the image resolution was seen to improve for most of the variable resolution examples. Also discussed are empirical fits for the weighting and the availability of the program, WEIGHT, used to generate the weighting for the individual frames. Finally, we include appendices describing the effects of clipping algorithms and a scheme for star/galaxy and cosmic-ray/star discrimination. scheme for star/galaxy and cosmic-ray/star discrimination.
Fischer, Philippe↗
A model-based approach for detection of objects in low resolution passive millimeter wave images
A model-based vision system to assist the pilots in landing maneuvers under restricted visibility conditions is described. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere, but their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. These data are exploited to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. Also analytical expressions were derived from the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.
Kasturi, Rangachar↗
A model-based approach for detection of objects in low resolution passive-millimeter wave images
We describe a model-based vision system to assist pilots in landing maneuvers under restricted visibility conditions. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere; but, their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. We exploit these data to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. We also derive analytical expressions for the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.
Tang, Yuan-Liang↗
A Mid-Infrared Imaging Survey of Embedded Young Stellar Objects in the (rho) Ophiuchi Cloud Core
Results of a comprehensive, new, ground-based mid-infrared imaging survey of the young stellar population of the (rho) Ophiuchi cloud are presented. Data were acquired at the Palomar 5m and at the Keck 10m telescopes with the MIRLIN and LWS instruments, at 0'.5 and 0'.25 resolutions, respectively. Of 172 survey objects, 85 were detected. Among the 22 multiple systems observed, 15 were resolved and their individual component fluxes determined. A plot of the frequency distribution of the detected objects with SED spectral slope shows that YSOs spend approx.4 x 10(exp 5) yr in the flat-spectrum phase, clearing out their remnant infall envelopes. Mid-infrared variability is found among a significant fraction of the surveyed objects and is found to occur for all SED classes with optically thick disks. Large-amplitude near-infrared variability, also found for all SED classes with optically thick disks, seems to occur with somewhat higher frequency at the earlier evolutionary stages. Although a general trend of mid-infrared excess and near-infrared veiling exists progressing through SED classes, with Class I objects generally exhibiting r(sub K) >= 1, flat-spectrum objects with r(sub K) >= 0.58, and Class III objects with r(sub K) =0, Class II objects exhibit the widest range of r(sub K) values, ranging from 0 <= r(sub K) <= 4.5. However, the highly variable value of veiling that a single source can exhibit in any of the SED classes in which active disk accretion can take place is striking and is direct observational evidence for highly time-variable accretion activity in disks. Finally, by comparing mid-infrared versus near-infrared excesses in a subsample with well-determined effective temperatures and extinction values, disk-clearing mechanisms are explored. The results are consistent with disk clearing proceeding from the inside out.
planetary systems↗
Who's Got the Bridge? - Towards Safe, Robust Autonomous Operations at NASA Langley's Autonomy Incubator
NASA aeronautics research has made decades of contributions to aviation. Both aircraft and air traffic management (ATM) systems in use today contain NASA-developed and NASA sponsored technologies that improve safety and efficiency. Recent innovations in robotics and autonomy for automobiles and unmanned systems point to a future with increased personal mobility and access to transportation, including aviation. Automation and autonomous operations will transform the way we move people and goods. Achieving this mobility will require safe, robust, reliable operations for both the vehicle and the airspace and challenges to this inevitable future are being addressed now in government labs, universities, and industry. These challenges are the focus of NASA Langley Research Center's Autonomy Incubator whose R&D portfolio includes mission planning, trajectory and path planning, object detection and avoidance, object classification, sensor fusion, controls, machine learning, computer vision, human-machine teaming, geo-containment, open architecture design and development, as well as the test and evaluation environment that will be critical to prove system reliability and support certification. Safe autonomous operations will be enabled via onboard sensing and perception systems in both data-rich and data-deprived environments. Applied autonomy will enable safety, efficiency and unprecedented mobility as people and goods take to the skies tomorrow just as we do on the road today.
Allen, B. Danette↗
UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations
Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.
Davila, Carlos G.↗
Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence
In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.
Mashiku, A.↗
Predicting Satellite Close Approaches Using Statistical Parameters in the Context of Artificial Intelligence
In order to ensure a sustainable use of low earth orbit in particular and near Earth space in general, reliable and effective close approach prediction be-tween space objects is key. Only this allows for efficient and timely colli-sion avoidance. Space Situational Awareness (SSA) for commercial and government missions will be facing the rapidly growing amount of small and potentially less agile satellites as well as debris in the near earth realm, such as the increase in CubeSat launches and upcoming large constellations. At the same time, space object detection capabilities are expected to increase significantly, allowing for the reliable detection of smaller objects, e.g. when the Air Force Space Fence radar becomes operational. In combination, the space object catalog is expected to increase tremendously in size. In this paper, we introduce an investigative approach based on the latest capabili-ties in artificial intelligence in fostering the potential for fast and accurate close approach predictions. We consider the study of statistical and infor-mation theory parameters in contrast and complementary to the classical probability of collision computation alone, in order to determine the feasi-bility of reliably predicting close approaches.
Mashiku, Alinda↗