A study of digital techniques for signal processing
Analysis and definition of digital techniques for signal processing
Schwartz, M.↗
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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.
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Signal Processing for Beam Loss Monitor System at Jefferson Lab
Ion Chamber and Photomultiplier Tube (PMT) are both used for beam loss monitor in the Machine Protection System (MPS) at Jefferson Lab. The requirements of signal processing of these detectors are different, so two VME-based signal processing boards, Beam Loss Monitor (BLM) board and Ion-Chamber board, were developed. The BLM board has fast response (< 1us) and 5 decades dynamic range from 10nA to 1 mA, while the Ion-Chamber board has 8 decades dynamic range from 100 pA to 10 mA and slower response. Both of boards provide functions of machine protection and beam diagnostics, and features of fast shutdown (FSD) interface, beam sync interface, built-in-self-test, remotely controlled bias signals, and on-board memory buffer.
Yan, J.↗
Preliminary development of digital signal processing in microwave radiometers
Topics covered involve a number of closely related tasks including: the development of several control loop and dynamic noise model computer programs for simulating microwave radiometer measurements; computer modeling of an existing stepped frequency radiometer in an effort to determine its optimum operational characteristics; investigation of the classical second order analog control loop to determine its ability to reduce the estimation error in a microwave radiometer; investigation of several digital signal processing unit designs; initiation of efforts to develop required hardware and software for implementation of the digital signal processing unit; and investigation of the general characteristics and peculiarities of digital processing noiselike microwave radiometer signals.
Stanley, W. D.↗
Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network
The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..
array↗
The ATAMM procedure model for concurrent processing of large grained control and signal processing algorithms
An overview is presented of a model for describing data and control flow associated with the execution of large-grained, decision-free algorithms in a special distributed computer environment. The ATAMM (Algorithm-To-Architecture Mapping Model) model provides a basis for relating an algorithm to its execution in a dataflow multicomputer environment. The ATAMM model features a marked graph Petri net description of the algorithm behavior with regard to both data and control flow. The model provides an analytical basis for calculating performance bounds on throughput characteristics which are demonstrated here.
Stoughton, John W.↗
Application of Temporal Moments and Other Signal Processing Algorithms to Analysis of Ultrasonic Signals Through Melting Wax.
Abstract not provided.
Lau, Sarah Josephine↗
Signal Processing Based Method for Real-Time Anomaly Detection in High-Performance Computing
Performance anomalies can manifest as irregular execution times or abnormal execution events for many reasons, including network congestion and resource contention. Detecting such anomalies in real-time by analyzing the details of performance traces at scale is impractical due to the sheer volume of data High-Performance Computing (HPC) applications produce. In this paper, we propose formulating HPC performance anomaly detection as a signal-processing problem where anomalies can be treated as noise. We evaluate our proposed method in comparison with two other commonly used anomaly detection techniques of varying complexity based on their detection accuracy and scalability. Since real-time in-situ anomaly detection at a large scale requires lightweight methods that can handle a large volume of streaming data, we find that our proposed method provides the best trade-off. We then implement the proposed method in Chimbuko, the first online, distributed, and scalable workflow-level performance trace analysis framework. We compare our proposed signal-based anomaly detection algorithm with two other methods using a function of their accuracy, F1 score, and detection overhead. Our experiments demonstrate that our proposed approach achieves a 99% improvement for the benchmark datasets and a 93% improvement with Chimbuko traces.
99 GENERAL AND MISCELLANEOUS↗
Onboard Signal Processing: Wave of the Future for Planetary Radio Science?
Future spacecraft-based radio observations of planetary surfaces, rings, and atmospheres could significantly benefit from recent technological advances in real-time digital signal processing (DSP) hardware. Traditionally, the radio observations have been carried out in a 'down link' configuration in which about 20-W spacecraft transmitted RF power illuminates the target of interest and the perturbed signal is collected at an Earth receiving station. The down link configuration was dictated by the large throughput of received data, corresponding to a relatively large recording band width (about 50 kHz) needed to capture the coherent and scattered signal components in the presence of trajectory, ephemeris, and measurement uncertainties. An alternative 'up link' configuration in which powerful Earth-based radio transmitters (20-200 kW) are used to illuminate the target and data are recorded on board a spacecraft could enhance the measurements' signal-to-noise ratio by a factor of about 1000, allowing a quantum leap in scientific capabilities. Various aspects of alternative signal processing technologies are discussed.
Marouf, E. A.↗
Digital signal processing algorithms for automatic voice recognition
The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.
Botros, Nazeih M.↗
Signal processing apparatus for multiplex transmission Patent
Sampling circuit for signal processing in multiplex transmission by Fourier analysis
Lim, L. Y.↗
Signal processing of aircraft flyover noise
A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a uniform level flyover is considered but the code can accept more general flight profiles. The effects of spectral smearing and its removal is discussed. Using data acquired from XV-15 tilt rotor flyover test comparisons are made showing the measured and corrected spectra. Frequency shifts are accurately accounted for by the method. It is shown that correcting for spherical spreading, Doppler amplitude, and frequency can give some idea about source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.
Kelly, Jeffrey J.↗
Signal processing of aircraft flyover noise
A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a level uniform flyover is considered in the study, but the code can accept more general flight profiles. The effects of spectral smearing and its removal are discussed. Using test data acquired from an XV-15 tilt-rotor flyover, comparisons are made between the measured and corrected spectra. Frequency shifts are accurately accounted for by the de-Dopplerization procedure. It is shown that by correcting for spherical spreading and Doppler amplitude, along with frequency, can give some idea about noise source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.
Kelly, J. J.↗
Implementation and Performance of GaAs Digital Signal Processing ASICs
The feasibility of performing high speed digital signal processing in GaAs gate array technology has been demonstrated with the successful implementation of a VLSI communications chip set for NASA's Deep Space Network. This paper describes the techniques developed to solve some of the technology and implementation problems associated with large scale integration of GaAs gate arrays.
Whitaker, William D.↗
Signal processing of anthropometric data
The Anthropometric Measurements Laboratory has accumulated a large body of data from a number of previous experiments. The data is very noisy, therefore it requires the application of some signal processing schemes. Moreover, it was not regarded as time series measurements but as positional information; hence, the data is stored as coordinate points as defined by the motion of the human body. The accumulated data defines two groups or classes. Some of the data was collected from an experiment designed to measure the flexibility of the limbs, referred to as radial movement. The remaining data was collected from experiments designed to determine the surface of the reach envelope. An interactive signal processing package was designed and implemented. Since the data does not include time this package does not include a time series element. Presently the results is restricted to processing data obtained from those experiments designed to measure flexibility.
Zimmermann, W. J.↗
Single-shot Quantum Signal Processing Interferometry
Quantum systems of infinite dimension, such as bosonic oscillators, provide vast resources for quantum sensing. Yet, a general theory on how to manipulate such bosonic modes for sensing beyond parameter estimation is unknown. We present a general algorithmic framework, quantum signal processing interferometry (QSPI), for quantum sensing at the fundamental limits of quantum mechanics by generalizing Ramsey-type interferometry. Our QSPI sensing protocol relies on performing nonlinear polynomial transformations on the oscillator's quadrature operators by generalizing quantum signal processing (QSP) from qubits to hybrid qubit-oscillator systems. We use our QSPI sensing framework to make efficient binary decisions on a displacement channel in the single-shot limit. Theoretical analysis suggests the sensing accuracy, given a single-shot qubit measurement, scales inversely with the sensing time or circuit depth of the algorithm. We further concatenate a series of such binary decisions to perform parameter estimation in a bit-by-bit fashion. Numerical simulations are performed to support these statements. Our QSPI protocol offers a unified framework for quantum sensing using continuous-variable bosonic systems beyond parameter estimation and establishes a promising avenue toward efficient and scalable quantum control and quantum sensing schemes beyond the NISQ era.
Physics↗
Signal processing and spectral modeling for the BeEST experiment
The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of 7 Be by precisely measuring the recoil energy of the 7 Li daughter. In Phase III, the BeEST experiment has been scaled from a singl superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. Here, we have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large datasets. Furthermore, this article presents the optimized procedures before unblinding the majority of the Phase III dataset to search for physics beyond the standard model.
6 ≤ A ≤ 19↗
Simplified signal processing for an airborne CO2 Doppler lidar
In the development of the National Center for Atmospheric Research (NCAR) airborne infrared lidar system (NAILS), we have emphasized a simple, modular design to suit the instrument to its mission of providing measurements of atmospheric structure and dynamics from an aircraft platform. Based on our research to this point, we believe that a significant simplification of the signal processing approach compared to that now used is possible by using high speed digitization of the signal. The purpose here is to place signal processing in the context of the overall system design and to explore the basis of the alternative technique so that the community can comment on the approach.
Schwiesow, R. L.↗
Model-Based Ultrasonic Signal Processing for the Nondestructive Evaluation of Additive Manufacturing Components
Ultrasonic testing (UT) for nondestructive evaluation (NDE) is a critical entity necessary to resolve both the quality and precision questions of complex parts evolving from the innovative additive manufacturing (AM) process. This modality provides the essential quantitative information for acceptance and potential flaw detectionof the part under investigation. A primary ingredient in UT besides the required precision robotic hardware for theacquisition of high quality measurement data is the underlying signal processing. It is here that much of the system performance capability resides. In this report,we discuss the basic steps in UT signal processing along with current and future capabilities that must be achieved in order to satisfy the critical demands created by the AM process.
42 ENGINEERING↗