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The Highly Compressed PolSAR Model
No full textAdditional scene information can be captured using fully polarimetric synthetic aperture radar (PolSAR) at the cost of significant increases in storage and data processing requirements. The typically sparse nature of PolSAR scenes makes compressed sensing (CS) techniques very attractive to help alleviate the increased processing and storage requirements. Here, the authors combine techniques for fast- and slow-time undersampling as well as the dropped-channel PolSAR CS technique to create a new highly compressed PolSAR model. Examples of both point target and real-world scenes are then used to demonstrate the model. Compression rates of up to 98.92% are observed for sufficiently sparse scenes
Analysis of Modeled 3D Solar Magnetic Field during 30 X/M-class Solar Flares
Get PDFUsing non-linear force free field (NLFFF) extrapolation, 3D magnetic fields were modeled from the 12-min cadence Solar Dynamics Observatory Helioseismic and Magnetic Imager (HMI) photospheric vector magnetograms, spanning a time period of 1 hour before through 1 hour after the start of 18 X-class and 12 M-class solar flares. Several magnetic field parameters were calculated from the modeled fields directly, as well as from the power spectrum of surface maps generated by summing the fields along the vertical axis, for two different regions: areas with photospheric |Bz|≥ 300 G (active region—AR) and areas above the photosphere with the magnitude of the non-potential field (BNP) greater than three standard deviations above BNP of the AR field and either the unsigned twist number |Tw| ≥ 1 turn or the shear angle Ψ ≥ 80° (non-potential region—NPR). Superposed epoch (SPE) plots of the magnetic field parameters were analyzed to investigate the evolution of the 3D solar field during the solar flare events and discern consistent trends across all solar flare events in the dataset, as well as across subsets of flare events categorized by their magnetic and sunspot classifications. The relationship between different flare properties and the magnetic field parameters was quantitatively described by the Spearman ranking correlation coefficient, rs. The parameters that showed the most consistent and discernable trends among the flare events, particularly for the hour leading up to the eruption, were the total unsigned flux ϕ), free magnetic energy (EFree), total unsigned magnetic twist (τTot), and total unsigned free magnetic twist (ρTot). Strong (|rs| ∈ [0.6, 0.8)) to very strong (|rs| ∈ [0.8, 1.0]) correlations were found between the magnetic field parameters and the following flare properties: peak X-ray flux, duration, rise time, decay time, impulsiveness, and integrated flux; the strongest correlation coefficient calculated for each flare property was 0.62, 0.85, 0.73, 0.82, −0.81, and 0.82, respectively
GENESIS: Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering
No full textImproved neutron inelastic scattering cross section data are needed to inform integral benchmark studies and advance applications in a wide variety of areas including nuclear energy, stockpile stewardship, nonproliferation, and space exploration. Neutron inelastic scattering also serves as a non-selective probe of low-lying nuclear structure. To help meet these needs, the Gamma Energy Neutron Energy Spectrometer for Inelastic Scattering (GENESIS) was constructed at the 88-Inch Cyclotron at Lawrence Berkeley National Laboratory. This array couples high-resolution -ray detectors and fast neutron detectors to achieve single and coincident n/ detection over a broad energy range. The current configuration of the array includes 26 organic liquid scintillators and four high-purity germanium detectors (two single-crystal and two four-crystal CLOVER detectors with two-fold segmentation). The array was constructed with minimal supporting material and designed to cover a wide range of secondary particle angles and energies with limited inter-element scattering. Data acquisition is accomplished using Mesytec MDPP-16 multi-channel high-resolution digital pulse processing modules. The array characteristics, including -ray and neutron energy resolution, timing resolution, and detection efficiency were measured and used to validate a Geant4 model of the array. The primary sources of neutron background and the uncertainties in the determination of incident and secondary neutron energy were assessed. GENESIS provides a new capability to address nuclear data needs and facilitates the advancement of a wide range of nuclear applications
A Leader-Follower Control Strategy Built and Refined using Relational Maneuver Primitives for Approximating Optimal Trajectories in Real-Time
No full textA Conceptual Design Workflow for Producing a Controllable 6DOF Simulation of a High-Speed Vehicle
No full textEdge Device CNN Classification Using Eventized RF Fingerprints
No full textFirst-step demonstration activity is presented here for an envisioned “event radio” capability that mimics neuromorphic event-based camera concepts. RFrequency (RF) eventization is introduced and its impact on Convolutional Neural Network (CNN) classification is assessed. Classification of eight commercial WirelessHART adapters is performed using sparsely populated event-based fingerprints containing 200-of-896 possible event detections-this is an important first-step toward realizing an envisioned neuromorphic-friendly Spiking Neural Network (SNN) capability supporting edge RF sensing. Superiority of Gabor Transform (GTX) features from collected bursts is evident in CNN classification results that include 1) classification accuracy greater than 90 percent using an average of 200 detected events per burst, versus 300 events per burst required for GTX-Direct eventization, and 2) a non-eventized versus RF eventized classification loss in classification accuracy of 4.11 percent for GTX-Derivative eventization, versus a loss of 5.42 percent in accuracy for GTX-Direct eventization. The CNN performance here motivates next-step event radio research aimed at demonstrating a neuromorphic-friendly SNN RF sensing capability using RF eventized fingerprints. Future demonstration objectives include completing the CNN-to-SNN transition, characterizing SNN classification performance, and performing hardware demonstrations. These objectives support achievement of an envisioned 1000X performance improvement that includes a 10X reduction in required power and 100X improvement in overall processing speed
Analysis of lithium aging using machine learning-enhanced spectroscopy techniques
No full textExcerpt: Lithium compounds such as lithium hydride (LiH) and lithium hydroxide (LiOH) have a wide range of industrial applications, but are highly reactive in environments with H2O and CO2. These reactions lead to the ingrowth of secondary lithium compounds, which can alter the homogeneity and affect the application of particular lithium chemicals. This study performed an exploratory analysis of different lithium compounds using laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy
Detector Mismatch Correction for the Calibration-Independent and Position-Insensitive Transmission/Reflection Method
No full textClassic methods for extracting material character-istics typically demand rigorous calibration, multiple samples, precise location measurements, etc. A recent research effort led by Zhao Caijun, Jiang Quanxing, and Jing Shenhui utilized a simple transmission/reflection method to extract high accuracy permittivity results from a Coaxial Line system. This method uses two uncalibrated scattering parameter measurements: one of the empty fixture and one of the sample at a single position. This paper extends the method to produce accurate permittivity results from a Rectangular Waveguide system once corrected for detector mismatch