The Role and Contributions of Energetic Neutral Atom (ENA) Imaging in Magnetospheric Substorm Research

Energetic Neutral Atom (ENA) imaging has contributed substantially to substorm research. This technique has allowed significant advances in areas such as observation and quantification of injected particle drift as a function of energy, observation of dynamics in the tail that are directly related to the effects of imposed (growth phase) and induced (expansion phase) electric fields on the plasma, the prompt extraction of oxygen from the ionosphere during substorms, the relationship between storms and substorms, and the timing of substorm ENA signatures. We present discussion of the advantages and shortcomings of the ENA technique for studying space plasmas. Although the technique is in its infancy, it is yielding results that enrich our understanding of the substorm process and its effects.     

Differential GPS/inertial navigation approach/landing flight testresults

In November 1990, a differential GPS/inertial flight test was conducted to acquire a system performance database and demonstrate automatic landing using an integrated differential GPS/INS with barometric and radar altimeters. Flight test results obtained from postflight data analysis are presented. These results include characteristics of DGPS/inertial error, using a laser tracker as a reference. In addition, data are provided on the magnitude of the differential correlations and vertical channel performance with and without radar altimeter augmentation. Flight test results show one sigma DGPS/inertial horizontal errors of 9 ft and one sigma DGPS inertial vertical errors of 15 ft. Without selective availability effects, the differential corrections are less than 10 ft and are dominated by receiver unique errors over the time period of an approach. Therefore, the one sigma performance of the autonomous GPS (8-ft horizontal and 20-ft vertical) is very similar to the DGPS/inertial performance. Postprocessed results also demonstrate significant improvements in vertical channel performance when GPS/inertial is aided with radar altimeter along with a low-resolution terrain map     

DNA damage and repair in oncogenic transformation by heavy ion radiation.

Energetic heavy ions are present in galactic cosmic rays and solar particle events. One of the most important late effects in risk assessment is carcinogenesis. We have studied the carcinogenic effects of heavy ions at the cellular and molecular levels and have obtained quantitative data on dose-response curves and on the repair of oncogenic lesions for heavy particles with various charges and energies. Studies with repair inhibitors and restriction endonucleases indicated that for oncogenic transformation DNA is the primary target. Results from heavy ion experiments showed that the cross section increased with LET and reached a maximum value of about 0.02 micrometer2 at about 500 keV/micrometer. This limited size of cross section suggests that only a fraction of cellular genomic DNA is important in radiogenic transformation. Free radical scavengers, such as DMSO, do not give any effect on induction of oncogenic transformation by 600 MeV/u iron particles, suggesting most oncogenic damage induced by high-LET heavy ions is through direct action. Repair studies with stationary phase cells showed that the amount of reparable oncogenic lesions decreased with an increase of LET and that heavy ions with LET greater than 200 keV/micrometer produced only irreparable oncogenic damage. An enhancement effect for oncogenic transformation was observed in cells irradiated by low-dose-rate argon ions (400 MeV/u; 120 keV/micrometer). Chromosomal aberrations, such as translocation and deletion, but not sister chromatid exchange, are essential for heavy-ion-induced oncogenic transformation. The basic mechanism(s) of misrepair of DNA damage, which form oncogenic lesions, is unknown.     

Simulation experiments of the effect of space environment on bacteriophage and DNA thin films.

The main goal of PUR experiment (phage and uracil response) is to examine and quantify the effect of specific space conditions on nucleic acid models. To achieve this an improved method was elaborated for the preparation of DNA and bacteriophage thin films. The homogeneity of the films was controlled by UV spectroscopy and microscopy. To provide experimental evidence for the hypothesis that interplanetary transfer of the genetic material is possible, phage T7 and isolated T7 DNA thin films have been exposed to selected space conditions: intense UVC radiation (lambda=254 nm) and high vacuum (10(-4) Pa). The effects of DNA hydration, conformation and packing on UV radiation damage were examined. Characteristic changes in the absorption spectrum, in the electrophoretic pattern of DNA and the decrease of the amount of PCR products have been detected indicating the photodamage of isolated and intraphage DNA.     

Sequence comparison techniques for multisensor data fusion andtarget recognition

A new class of techniques for multisensor fusion and target recognition is proposed using sequence comparison by dynamic programming and multiple model estimation. The objective is to fuse information on the kinematic state and “nonkinematic” signature of unclassified targets, assessing the joint likelihood of all observed events for recognition. Relationships are shown to previous efforts in pattern recognition and state estimation. This research applies “classical” speech processing-related and other sequence comparison methods to moving target recognition, extends the efforts of previous researchers through improved fusion with kinematic information, relates the proposed techniques to Bayesian theory, and applies parameter identification methods to target recognition for improved understanding of the subject in general. The proposed techniques are evaluated and compared with existing approaches using the method of generalized ambiguity functions, which lends to a form of Cramer-Rao lower bound for target recognition     

AFIT neural network research

A brief summary of research done at the Air Force Institute of Technology (AFIT) in the area of neural networks is provided. It has been shown that backpropagation, used for feedforward artificial neural networks, is just a degenerate version of an extended Kalman filter, and that networks can do about as well as the optimum statistical classification technique. A method of finding the importance of features for use by a neural network classifier has been determined. Techniques for using neural networks for image segmentation have been developed. In optical pattern recognition, techniques that allow the processing of real FLIR (forward-looking infrared) images with existing binary spatial light modulators have been devised. An optical direction of arrival detector applicable to laser illumination direction determination has been designed and tested; the design is similar to a fly's eye. Coated mirrors for the optical confocal Fabry-Perot interferometer have been designed, specified, fabricated, and installed. Significant progress has been made in the use of neural networks for processing multiple-feature sets for speech recognition     

A wavelet multiresolution analysis for spatio-temporal signals

The wavelet filters of the conventional 3D multiresolution analysis possess homogeneous spatial and temporal frequency characteristics which limits one's ability to match filter frequency characteristics to signal frequency behavior. Also, the conventional 3D multiresolution analysis employs an oct-tree decomposition structure which restricts the analysis of signal details to identical resolutions in space and time. This paper presents a 3D wavelet multiresolution analysis constructed from nonhomogeneous spatial and temporal filters, and an orthogonal sub-band coding scheme that decouples the spatial and temporal decomposition processes     

Fiber optic fence sensor developments

Many detection technologies have been employed for perimeter detection, to sensitize a barrier. These outdoor perimeter fence detection sensors must reliably detect intruders attempting to cut or climb the barrier, while ignoring the effects of environmental noise, including nearby activity. In recent conference proceedings, the new IntelliFIBER/spl trade/ fiber optic based product was introduced and compared with previous technologies. IntelliFIBER is designed to provide the advantages of a nonconductive "dielectric" cable sensor, e.g., resistance to electromagnetic interference and the ability to provide longer cable zones. It utilizes the proven processor of the Intelli-FLEX/spl trade/ triboelectric cable fence sensor, which provides relay or bidirectional networked serial communications and is compatible with its calibration module. IntelliFIBER also capitalizes on the Intelli-FLEX's adaptive detection algorithms that were developed through extensive field-testing, to provide exceptional immunity to environmental alarms while still detecting the skilled intruder.     

TerraSAR-X active radar ground calibrator system

In April 2006, the TerraSAR-X satellite was launched. This paper describes the development of a novel and highly integrated, digitally-controlled active SAR system calibrator (DARC). It consists of both an active transponder path for absolute radiometric calibration and a calibrated receiver chain for antenna pattern evaluation of the satellite antenna. A total of 16 active transponder and receiver systems and 17 receiver-only systems will be fabricated for a calibration campaign in 2006.     

Almost instant time inference for hybrid partially dynamic Bayesian networks

A Bayesian network (BN) is a compact representation for probabilistic models and inference. They have been used successfully for many military and civilian applications. It is well known that, in general, the inference algorithms to compute the exact a posterior probability of a target node given observed evidence are either computationally infeasible for dense networks or impossible for general hybrid networks. In those cases, one either computes the approximate results using stochastic simulation methods or approximates the model using discretization or a Gaussian mixture model before applying an exact inference algorithm. This paper combines the concept of simulation and model approximation to propose an efficient algorithm for those cases. The main contribution here is a unified treatment of arbitrary (nonlinear non-Gaussian) hybrid (discrete and continuous) BN inference having both computation and accuracy scalability. The key idea is to precompile the high-dimensional hybrid distribution using a hypercube representation and apply it for both static and dynamic BN inference. Since the inference process essentially becomes a combination of table look-up and some simple operations, the method is shown to be extremely efficient. It can also he scaled to achieve any desirable accuracy given sufficient preprocessing time and memory for the cases where exact inference is not possible