Search NASA⌕ Search

SEARCH · Search NASA

Results for “Signal Reconstruction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Quantifying Uncertainties Through Advanced Theoretical Analysis for Image and Signal Reconstruction, NLV-02-15, Year 2 of 2

Presentation describes project to (1) adapt accelerated matrix-free linear system solvers for applying new statistical approaches to very large–scale problems, (2) characterize the degree to which new statistical methods are superior to classical methods in respect to the sensitivity to “tuning parameters,” and (3) develop a new mathematical theory and associated numerical methods for computing the point spread function of an x-ray imaging system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Robust Resilient Signal Reconstruction under Adversarial Attacks

We consider the problem of signal reconstruction for a system under sparse signal corruption by a malicious agent. The reconstruction problem follows the standard error coding problem that has been studied extensively in the literature. We include a new challenge of robust estimation of the attack support. The problem is then cast as a constrained optimization problem merging promising techniques in the area of deep learning and estimation theory. A pruning algorithm is developed to reduce the "false positive" uncertainty of data-driven attack localization results, thereby improving the probability of correct signal reconstruction. Sufficient conditions for the correct reconstruction and the associated reconstruction error bounds are obtained for both exact and inexact attack support estimation. Moreover, a simulation of a water distribution system is presented to validate the proposed techniques.

Robust, Signal reconstruction, Resilient estimator↗
NASA NTRS1989

Application of adaptive least-squares algorithm to multi-element array signal reconstruction

Results are presented in terms of the performance improvement of a multi-feed array configuration over the usual single feed system when an adaptive least-squares algorithm is applied for the signal reconstruction. Two versions of the least-squares algorithm are presented, one of which is based on the maximization of the signal-to-noise ratio while the other is based on the deconvolution of received signal field. These algorithms were developed for the purpose of minimizing degradations arising from various sources, which can severely limit the performance (gain) of a single-feed system.

Kumar, R.↗
NASA NTRS1998

Real-Time Sensor Validation, Signal Reconstruction, and Feature Detection for an RLV Propulsion Testbed

A real-time system for validating sensor health has been developed in support of the reusable launch vehicle program. This system was designed for use in a propulsion testbed as part of an overall effort to improve the safety, diagnostic capability, and cost of operation of the testbed. The sensor validation system was designed and developed at the NASA Lewis Research Center and integrated into a propulsion checkout and control system as part of an industry-NASA partnership, led by Rockwell International for the Marshall Space Flight Center. The system includes modules for sensor validation, signal reconstruction, and feature detection and was designed to maximize portability to other applications. Review of test data from initial integration testing verified real-time operation and showed the system to perform correctly on both hard and soft sensor failure test cases. This paper discusses the design of the sensor validation and supporting modules developed at LeRC and reviews results obtained from initial test cases.

Jankovsky, Amy L.↗
NASA NTRS1977

Hologram-reconstruction signal enhancement

Principle of heterodyne detection is used to combine object beam and reconstructed virtual image beam. All light valves in page composer are opened, and virtual-image beam is allowed to interfere with light from valves.

Mezrich, R. S.↗
NASA NTRS1992

Multi-element array signal reconstruction with adaptive least-squares algorithms

Two versions of the adaptive least-squares algorithm are presented for combining signals from multiple feeds placed in the focal plane of a mechanical antenna whose reflector surface is distorted due to various deformations. Coherent signal combining techniques based on the adaptive least-squares algorithm are examined for nearly optimally and adaptively combining the outputs of the feeds. The performance of the two versions is evaluated by simulations. It is demonstrated for the example considered that both of the adaptive least-squares algorithms are capable of offsetting most of the loss in the antenna gain incurred due to reflector surface deformations.

Kumar, R.↗
DOE OSTI2024

Lambda baryon production in neutrino-nucleus interactions and light signals reconstruction in the Short-Baseline Near Detector

The field of neutrino physics is nowadays entering the era of precision measurements, with new detectors capable of capturing neutrino interactions with unprecedented detail and high intensity neutrino beams. Liquid Argon Time Projection Chambers (LArTPCs) have become one of the main neutrino detection technologies, providing excellent imaging capabilities and particle identification. The Short-Baseline Near Detector (SBND) at Fermilab is a LArTPC experiment designed to capture neutrinos from the Booster Neutrino Beam (BNB). Its proximity to the beam target (110\,m) and large size (112\,ton) enable the recording of millions of neutrino interactions annually. SBND provides the highest statistics worldwide for neutrino-argon cross-section measurements, facilitating the study of rare channels like Cabibbo-suppressed quasielastic hyperon production. Specifically, this thesis focuses on neutral $\Lambda$ baryon production for which only tens of events have been observed up to date. Our work introduces a novel selection strategy leveraging LArTPC imaging capabilities to identify the distinctive decay signatures of $\Lambda$ baryons, enhancing sensitivity to this channel. Besides being a very mature technology, LArTPCs are an evolving technology. Part of the focus of the new developments lies in harnessing the potential of scintillation light signals. The Photon Detection System (PDS) in SBND has been designed to provide an efficient detection of the scintillation light, representing a major R\&D opportunity in the LArTPC community. Its design provides a high and more uniform light yield, an excellent timing resolution and an independent 3D reconstruction of the events, including the drift coordinate, using exclusively the light signals. This work presents the first comprehensive study of the SBND PDS capabilities. The new developments in the simulation and reconstruction of the light signals in SBND are presented. The whole chain is applied to accurately tag neutrino events through timing information, with a predicted resolution $\mathcal{O}$(2\,ns), and ultimately retrieve the pulse structure of the BNB.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors de- signed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two- dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also searching for nucleon decay are important uses of automated reconstruction algorithms. Be- cause the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques. Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Automated Reconstruction, Signal Processing and Particle Identification in DUNE

Liquid Argon TPC (LArTPC) technology is increasingly prevalent in large-scale detectors designed to observe neutrino scattering events induced by accelerators or by natural sources. LArTPCs consist of a very high fraction of active detector material with spatial resolutions on the order of a few millimeters. Three-dimensional interactions are imaged in multiple two-dimensional views by the process of projection onto planes of wires. The goal of automated reconstruction is to correctly classify each neutrino scattering event by the flavor of the incoming neutrino, to separate charged-current events from neutral-current and other backgrounds, and to measure the energies of the incoming neutrinos. Detection of neutrinos from supernova bursts and also seaching for nucleon decay are important uses of automated reconstruction algorithms. Because the amount of spatial detail is high and the amount of scattering is high, this reconstruction presents many challenges that are now being investigated with sophisticated techniques.Signal processing, track and shower identification, particle identification, and event classification by a variety of innovative algorithms are reviewed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Sparse signal reconstruction from polychromatic X-ray CT measurements via mass attenuation discretization

We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer’s law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth ℓ{sub 1}-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refinement allows us to successfully handle the characteristic lines (Dirac impulses) in the incident energy density spectrum. We compare the proposed method with the standard filtered backprojection, which ignores the polychromatic nature of the measurements and sparsity of the image density map. Numerical simulations using both realistic simulated and real x-ray ct data are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Simulation Studies Of Photon Signal Reconstruction In The DUNE Single Phase Far Detector With Xe Doping

Xenon when doped to argon has the potential to increase the effectiveness of scintillation systems in liquid argon time projection chambers (LArTPC). To test the potential improvements, a simulation study was conducted. A simulation of light going through liquid Argon and Xenon photon libraries (photon libraries are used to reduce the amount of computational power needed for interactions that produce a large amount of photons), comparing differences in their properties. The study found more light being emitted in a shorter time by Xe than by Ar with less attenuation present. Preliminary results show lower efficiency of Ar at closer distances. It's unclear whether this is due to inherit properties of the Xe or a result of selection cuts not being optimized. These potential improvements are being looked into for future neutrino experiments such as the Deep Underground Neutrino Experiment (DUNE).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Quantifying Uncertainties through Advanced Theoretical Analysis for Image and Signal Reconstruction NLV-02-15, Year 1 of 2

Presentation describes project to (1) adapt accelerated matrix-free linear system solvers for applying new statistical approaches to very large–scale problems, (2) characterize the degree to which new statistical methods are superior to classical methods in respect to the sensitivity to “tuning parameters,” and (3) develop a new mathematical theory and associated numerical methods for computing the point spread function of an x-ray imaging system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Autoencoder-Based Sensor Drift Detection and Mitigation for Resilient Charging Systems

This work presents an autoencoder-based approach for sensor signal reconstruction and drift detection for charging systems. The proposed strategy is implemented within a Simulink-based system framework and evaluated under multiple operating conditions. An autoencoder with 8 neurons in the bottleneck layer is adopted, achieving accurate reconstruction across 10 variables and strong agreement with the physical sensor readings under normal conditions. In the case of a sensor fault, the autoencoder reconstruction remains closer to the expected true value compared to the corrupted measurement. Furthermore, feeding the autoencoder-reconstructed signal value back into the control framework in place of the faulty sensor signal leads to improved power monitoring. These results highlight the potential of autoencoder-based virtual sensing to extend the concept of resiliency to all components of the charging system, including sensors.

Rezende Da Costa Reis Kimpara, Renata [ORNL] (ORCI↗
DOE OSTI2014

Robust frequency diversity based algorithm for clutter noise reduction of ultrasonic signals using multiple sub-spectrum phase coherence

This paper presents a robust frequency diversity based algorithm for clutter reduction in ultrasonic A-scan waveforms. The performance of conventional spectral-temporal techniques like Split Spectrum Processing (SSP) is highly dependent on the parameter selection, especially when the signal to noise ratio (SNR) is low. Although spatial beamforming offers noise reduction with less sensitivity to parameter variation, phased array techniques are not always available. The proposed algorithm first selects an ascending series of frequency bands. A signal is reconstructed for each selected band in which a defect is present when all frequency components are in uniform sign. Combining all reconstructed signals through averaging gives a probability profile of potential defect position. To facilitate data collection and validate the proposed algorithm, Full Matrix Capture is applied on the austenitic steel and high nickel alloy (HNA) samples with 5MHz transducer arrays. When processing A-scan signals with unrefined parameters, the proposed algorithm enhances SNR by 20dB for both samples and consequently, defects are more visible in B-scan images created from the large amount of A-scan traces. Importantly, the proposed algorithm is considered robust, while SSP is shown to fail on the austenitic steel data and achieves less SNR enhancement on the HNA data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗