KEYWORDS: Digital signal processing, Reconfigurable computing, Sensors, Image segmentation, Image processing, Remote sensing, Field programmable gate arrays, Feature extraction, Signal processing, Algorithm development
Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of spectral bands with millions of pixels. These data sets show great promise for remote sensing applications, but require new and computationally intensive processing. The goal of the Deployable Adaptive Processing Systems (DAPS) project at Los Alamos National Laboratory is to develop advanced processing hardware and algorithms for high-bandwidth sensor applications. The project has produced electronics for processing multi- and hyper-spectral sensor data, as well as LIDAR data, while employing processing elements using a variety of technologies. The project team is currently working on reconfigurable computing technology and advanced feature extraction techniques, with an emphasis on their application to image and RF signal processing. This paper presents reconfigurable computing technology and advanced feature extraction algorithm work and their application to multi- and hyperspectral image processing. Related projects on genetic algorithms as applied to image processing will be introduced, as will the collaboration between the DAPS project and the DARPA Adaptive Computing Systems program. Further details are presented in other talks during this conference and in other conferences taking place during this symposium.
This is a report on work in progress. Spectral recognition is central to many areas of science and technology. Classical spectral recognition analysis techniques (least squares, partial least squares, etc.) are sensitive to offset and gain drifts and errors. This sensitivity can cause excessive costs for spectrometer resources and calibrations. Neural techniques relieve some of this sensitivity but none approach human competence. It is desirable to mimic human spectral analysis not only to improve the results but to minimize detector constraints and costs. We suggest that the first step in human analysis is peak detection. We are exploring the 1D PCNN as a peak segmenter for spectral peak finding in the presence of noise and drifts in gain and offset. We present results of 1D pulse coded neural network peak detection with both simulated and actual static spectra. We also use the PCNN to form a scale and translation invariant feature vector that may be decomposed using classical techniques such as least squares. Finally, we propose using a PCNN to exploit the temporal aspects of spectral acquisition.
We consider the problem of using the information from two time series, each characterizing a different physical quantity, to predict the future state of the system and, based on that information, to detect and classify anomalous events. We stress the application of principal components analysis (PCA) to analyze and combine data from the different sensors. We construct both linear and nonlinear predictors. In particular, for linear prediction we use the least-mean-square (LMS) algorithm and for nonlinear prediction we use both back-propagation (BP) networks and fuzzy predictors (FP). As an application, we consider the prediction of gamma counts from past values of electron and gamma counts recorded by the instruments of a high altitude satellite.
The FORTE' (fast on-orbit recording of transient events) small satellite experiment scheduled for launch in October 1995 will attempt to measure and classify electromagnetic transients as sensed from space. The FORTE' payload will employ an event classifier to perform onboard classification of radio frequency transients from terrestrial sources such as lightning. These transients are often dominated by a constantly changing assortment of man-made `clutter' such as TV, FM, and radar signals. The FORTE' event classifier, or EC, uses specialized hardware to implement various signal processing and neural network algorithms. The resulting system can process and classify digitized records of several thousand samples onboard the spacecraft at rates of about a second per record. In addition to reducing downlink rates, the EC minimizes command uplink data by normally using uploaded algorithm sequences rather than full code modules (although it is possible for full code modules to be uploaded from the ground). The FORTE' event classifier experiment combines science and engineering in an evolutionary step toward useful and robust adaptive processing systems in space.
We present a small Explorer mission, Imagers for the Magnetosphere, Aurora, and Plasmasphere (IMAP), to provide the first global magnetospheric images that will allow a systematic study of major regions of the magnetosphere, their dynamics, and their interactions. The mission objective is to obtain simultaneous images of the inner magnetosphere (ring current and trapped particles), the plasmasphere, the aurora, and auroral upflowing ions. The instruments
are (1) a Low Energy Neutral Particle Imager for imaging H and O atoms, separately, in the energy range of ~1 to 30 keV, in several energy passbands; (2) an Energetic Neutral Particle Imager for imaging H atoms in the energy range ~15 to 200 keV and, separately, O atoms in the energy range ~60 to 200 keV, each in several energy passbands; (3) an Extreme-Ultraviolet Imager to obtain images of the plasmasphere (the distribution of cold He+) by means of He+ (30.4 nm) emissions; and (4) a Far-Ultraviolet Imaging Monochromator to provide images of the aurora and the geocorona. All images will be obtained with time and spatial resolutions appropriate to the global and macroscale structures to be observed. IMAP promises new quantitative analyses that will provide great advances in insight and knowledge of global and macroscale magnetospheric parameters. The results expected from IMAP will provide the first large-scale visualization of the ring current, the trapped ion populations, the plasmasphere, and the upflowing auroral ion population. Such images, coupled with simultaneously obtained auroral images, will also provide the initial opportunity to globally interconnect these major magnetospheric regions. The time sequencing of IMAP images will also provide the initial large-scale visualization of magnetospheric dynamics, both in space and time.
Imaging of the space plasma environment via low-energy neutral atoms (LENAs) promises to revolutionize the way in which largescale space plasma phenomena are viewed and understood. LENAs are produced by charge exchange between plasma ions (less than tens of kilo-electron-volts) and cold geocoronat neutrals; these LENAs radiate outward in all directions from their points of origin. Previously developed methods for imaging higher energy neutrals are not suitable for observing the majority of the terrestrial magnetosphere, which is comprised primarily of lower energy plasma populations. This paper briefly describes both the direct and indirect techniques that have been suggested for imaging LENAs to date. We then examine in more detail the most advanced of these techniques appropriate for magnetospheric imaging, indirect detection based on ionization of LENAs as they transit ultrathin foils. Such a LENA imager consists of four basic components: (1) a biased collimator to remove the ambient charged particles and set the azimuthal field of view; (2) an ultrathin foil, which ionizes a portion of the incident LENAs; (3) an electrostatic analyzer to reject UV light and set the energy passband; and (4) a coincidence position detector to measure converted LENAs while rejecting noise and penetrating radiation.
Imaging of the terrestrial magnetosphere is possible through the detection of low-energy neutral atoms (LENA5) produced by charge exchange between magnetospheric plasma ions and neutral atoms of the Earth's geocorona. We present calculations of both hydrogen and oxygen line-of-sight LENA fluxes expected on orbit for various plasma regimes as predicted by the Rice University Magnetospheric Specification Model. To decrease the required computation time, we are in the process of adapting our code for massively parallel computers. The speed gains achieved from parallel algorithms are substantial, and we present results from computational runs on the Connection Machine CM-2 data parallel supercomputer. We also estimate expected image count rates and image quality based on realistic instrument geometric factors, energy passbands, neutral atom scattering in the instrument, and image accumulation intervals. The results indicate that LENA imaging instruments will need a geometric factor (G) on the order of 0.1 cm2 sr eV/eV to be capable of imaging storm time ring currents, and a G of 1.0 cm2 sr eV/eV in order to image the quiet time ring current fluxes, ion injections from the tail, and subsequent ion drifts toward the dayside magnetopause.
Recently proposed low-energy neutral atom (LENA) imaging techniques rely on collisional processes to convert LENAs into ions to separate the neutrals from the intense UV radiation background. At low energies, these collisional processes have poor conversion efficiencies and limit the angular resolution of these devices. However, if the intense UV light background can be suppressed, direct LENA detection is possible. We present results from a series of experiments designed to develop a novel filtering structure based on free-standing gold transmission gratings. If the grating period is sufficiently small, the gratings can substantially polarize UV light in the wavelength range 300 to 1500 Å. If a second grating is placed behind the first grating with its axis of polarization oriented perpendicular to that of the first, considerable attenuation of the UV radiation is achievable. The neutrals pass through the remaining open area of two gratings and are directly detected. We have obtained nominal 2000-Å-period (1000-Å bars with 1000-Å slits) gratings and measured their UV and atomic transmission characteristics. The geometric factor of a LENA imager based on this technology is comparable to that of other proposed LENA imagers, with a significantly better angular resolution.
Low energy neutral atoms (LENAs) are produced in space plasmas by charge exchange between the ambient magnetospheric plasma ions and cold neutral atoms. Under normal conditions these cold neutrals come from the terrestrial geocorona, a shroud of few-eV hydrogen atoms surrounding the Earth. As a consequence of this charge exchange, it has become possible to remotely image many regions of the magnetosphere for the first time utilizing recently developed LENA imaging technology. In addition to the natural hydrogen geocorona, conventional explosions and maneuvering thruster firings can also introduce large amounts of cold gas into the space environment. In this paper we examine whether such potentially clandestine activities could also be remotely observed for the first time via LENA imaging. First, we examine the fluxes of LENAs produced in the space environment from a conventional explosion. Then we review the present state of the art in the emerging field of LENA detection and imaging. We conclude that the sensitivities for present LENA imager designs may be just adequate for detecting some mad-made releases. With additional improvements in LENA detection capabilities, this technique could become an important new method for monitoring for conventional explosions, as well as other man-made neutral releases, in the space environment.
The development of instrumentation for magnetosphenc imagery and the design of future missions demands increasingly realistic simulations of the EUV and ENA emissions from magnetospheric ion populations. Relatively "cold" ion populations (E<5OeV) that fill the plasmasphere can, in principle, be imaged in the re-radiated solar lines of He+(304A) and O+(834A). "Hot" ion populations (E<lkeV) can be imaged using the energetic neuiral atoms produced when energelic singly-charged ions are neutralized in a charge-exchange collision with the cloud of exospheric H-atoms (the hydrogen geocorona) that suffuses the magnetosphere. We have responded to the need for increasing realism in simulations by incorporating elements of the Rice Convection Model (RCM) of magnetospheric dynamics into our images. The model, developed over the past decade by the Rice University, takes as its inputs the variation of measured magnetospheric indices and follows the transport and energy changes of the ion populations over the evolution of magnetic storms. We actually use a stream-lined version of the RCM, called the Magnetic Specification Model (MSM) that does not compute a self-consistent electric field, but utilizes phenomenological convection pauerns. The result is a sequence of simulated images as they would be obtained throughout a magnetic storm along a representative spacecraft orbit. These images set the requirements for sensitivity, angular resolution, energy pass-bands, etc., that must be met by imaging instruments on future magnetospheric missions. We then address the critical question of the extraction from the images of physical parameters describing the ion distribution functions. We report our progress in the development of computer-automated algorithms that extract the optimal set of parameters by minimizing a difference function between images simulated from a mathematical model of the ion distribution and "data" images simulated from MSM runs using inputs from actual geomagnetic storms.
Recently proposed low energy neutral atom (LENA) imaging techniques use a collisional process to convert the low energy neutrals into ions before detection. At low energies, collisional processes limit the angular resolution and conversion efficiencies of these devices. However, if the intense ultraviolet light background can be suppressed, direct LENA detection is possible. We present results from a series of experiments designed to develop a novel filtering structure based on free-standing transmission gratings. If the grating period is sufficiently small, free standing transmission gratings can be employed to substantially polarize ultraviolet (UV) light in the wavelength range 300 angstroms to 1500 angstroms. If a second grating is placed behind the first grating with its axis of polarization oriented at a right angle to the first's, a substantial attenuation of UV radiation is achievable. The neutrals will pass through the remaining open area of two gratings and be detected without UV background complications. We have obtained nominal 2000 angstroms period (1000 angstroms bars with 1000 angstroms slits) free standing, gold transmission gratings and measured their UV and atomic transmission characteristics. The geometric factor of a LENA imager based on this technology is comparable to that of other proposed LENA imagers.
Imaging of the terrestrial magnetosphere can be performed by detection of low energy neutral atoms (LENAs) that are produced by charge exchange between magnetospheric plasma ions and cold neutral atoms of the Earth's geocorona. As a result of recent instrumentation advances it is now feasible to make energy-resolved measurements of LENAs from less than 1 keV to greater than 30 keV. To model expected LENA fluxes at a spacecraft, we initially used a simplistic, spherically symmetric magnetospheric plasma model. We now present improved calculations of both hydrogen and oxygen line-of-sight LENA fluxes expected on orbit for various plasma regimes as predicted by the Rice University Magnetospheric Specification Model. We also estimate expected image count rates based on realistic instrument geometric factors, energy passbands, and image accumulation intervals. The results indicate that presently proposed LENA instruments are capable of imaging of storm time ring current and potentially even quiet time ring current fluxes, and that phenomena such as ion injections from the tail and subsequent drifts toward the dayside magnetopause may also be deduced.
Detection of low energy neutral atoms (LENAs) produced by the interaction of the Earth's geocorona with ambient space plasma has been proposed as a technique to obtain global information about the magnetosphere. Recent instrumentation advances reported previously1 and in these proceedings (McComas et a!., Funsten et aL) provide an opportunity for detecting LENAs in the energy range of <1 keV to -5O keY. In this paper, we present results from a numerical model which calculates line of sight LENA fluxes expected at a remote orbiting spacecraft for various magnetospheric plasma regimes. This model uses measured charge exchange cross sections, either of two neutral hydrogen geocorona models, and various empirical models of the ring current and plasma sheet to calculate the contribution to the integrated directional flux from each point along the line of sight of the instrument. We discuss implications for LENA imaging of the magnetosphere based on these simulations
Energetic neutral atom (ENA) and low energy neutral atom (LENA) imaging of space plasmas are emerging new technologies which promise to revolutionize the way we view and understand large scale space plasma phenomena and dynamics. ENAs and LENAs are produced in the magnetosphere by charge exchange between energetic and plasma ions and cold geocoronal neutrals. While imaging techniques have been previously developed for observing ENAs with energies above several tens of keV, most of the ions found in the terrestrial magnetosphere have lower energies. We recently suggested that LENAs could be imaged by first converting the neutrals to ions and then electrostatically analyzing them to reject the UV background. In this paper we extend this work to examine in detail the sensor elements needed to make an LENA imager. These elements are 1) a biased collimator to remove the ambient plasma ions and electrons and set the azimuthal field-of-view; 2) a charge modifier to convert a portion of the incident LENAs to ions; 3) an electrostatic analyzer to reject UV light and set the energy passband; and 4) a coincidence position detector to measure converted LENAs while rejecting noise and penetrating radiation; all are flight proven technologies. We also examine the issue of LENA imager sensitivity and describe ways of optimizing sensitivity in the various sensor components. Finally, we demonstrate how these general considerations are implemented by describing one relatively straighiforward design based on a hemispherical electrostatic analyzer