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Unipolar pulse and bipolar noise testing of wideband signal noise conditioner (MC476-0132-0034)
Information is presented on performance characteristics of the shuttle orbiter wideband signal conditioner when subjected to special types of input signals. Design analysis of the signal flow path through the signal conditioning amplifier was performed followed by acutal testing of the amplifier with various signal inputs. Results indicate that the signal conditioner should perform acceptably if the shuttle orbiter flight vibration signal levels are in accord with preflight predictions.
Signal noise in pure fluid amplifiers research report no. 1
Signal noise in pure fluid amplifiers, signal function generator, fluid transmission lines, closed loop control, and related instrumentation and equipment
Linear signal noise summer accurately determines and controls S/N ratio
Linear signal noise summer precisely controls the relative power levels of signal and noise, and mixes them linearly in accurately known ratios. The S/N ratio accuracy and stability are greatly improved by this technique and are attained simultaneously.
Identifying Different Classes of Seismic Noise Signals Using Unsupervised Learning
Abstract Proper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources.
Analysis of pump-to-signal noise transfer in two-stage ultra-broadband optical parametric chirped-pulse amplification
In optical parametric chirped-pulse amplification (OPCPA), pump temporal intensity modulation is transferred to the chirped-signal spectrum via instantaneous parametric gain and results in contrast degradation of the recompressed signal. We investigate, for the first time to our knowledge, the pump-to-signal noise transfer in a two-stage ultra-broadband OPCPA pumped by a single laser and show the dependence of pump-induced signal noise, characterized both before and after pulse compression, on the difference in pump-seed delay in the two stages. We demonstrate an up-to-15-dB reduction of the pump-induced contrast degradation via pump-seed delay optimization. Experiments and simulations show that, even when parametric amplifiers are operated in saturation, the pump-seed delay can be used to minimize the pump-induced contrast degradation that is attributed largely to the noises from the unsaturated edges of the pulse and that of the beam.
Using time reversal with long duration broadband noise signals to achieve high amplitude and a desired spectrum at a target location
Time Reversal (TR) is a signal processing technique that can be used to focus acoustic waves to a specific location in space, with most applications aiming to create an impulsive focus. Here, this study instead aims to focus long-duration noise signals using TR. This paper seeks to generate higher amplitude noise at a desired location over an existing method of broadcasting equalized noise. Additionally, this paper explores various characteristics associated with focusing long duration noise using TR. The dependence of the focal amplitude on the duration of the focused signal is explored as well as the implications of using multiple sources when focusing noise. The focal amplitude decreases with longer duration and then levels off when the duration exceeds a few seconds. Coherent addition of focused noise is observed if all loudspeakers have coherent noise signals convolved with their reversed impulse responses. Lastly, focusing noise with a desired spectrum is explored.
Noise signal identification in time projection chamber data using deep learning model
Deep learning has been employed in various scientific fields and has provided promising results. Here, in this study, a deep learning classifier was implemented to improve the quality of data obtained from a time projection chamber. Digital waveforms of the detected signals were classified into the following three categories: particles, noises, and particles piled up with noises. A simple 1-dimensional convolutional neural network was developed for the classification. The model demonstrated an excellent performance on the test dataset. Its practical performance was also examined using track images and particle identification plots by comparing the original and clean data without the noise signals. The comparison clearly showed that the deep learning model improved the quality of data. The current study presents an effective application of the deep learning model for the time projection chamber data.
Experimental atmospheric absorption values from aircraft flyover noise signals
Analysis of aircraft noise recordings to determine experimental values of atmospheric sound absorption
The effect of signal noise on the remote sensing of Foliar biochemical concentration
Spectral measurements made using an imaging spectrometer contain systematic and random noise, while the former can be corrected the latter remains a source of error in the remotely sensed signal. A number of investigators have tried to determine the signal-to-noise-ratio (SNR) of the instrument, or the resultant imagery. However, the level of noise at which spectra are too noisy to be useful is not usually determined. The first attempt was by Goetz and Calvin, who suggested that the depth of the absorption feature should be at least an order of magnitude greater than the noise and more recently Dekker suggested a SNR of around 600:1 was required in visible/near infrared wavelengths to measure a 1/gl change in chlorophyll a concentration water. The wide range of applications of imaging spectroscopy make it difficult to set SNR specifications as they are dependent on a number of factors, one of the most important being reflectance of a particular target. For example, the SNR of imagery for vegetated targets is relatively low simply because vegetation has a relatively low level of reflectance. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) is being used to estimate the concentration of biochemicals within vegetation canopies. This paper reports a study undertaken to identify first, wavebands that were highly correlated with foliar biochemical concentration and second, to determine how sensitive these correlations were to sensor noise.
Orbiter CCTV video signal noise analysis
The amount of steady state and transient noise which will couple to orbiter CCTV video signal wiring is predicted. The primary emphasis is on the interim system, however, some predictions are made concerning the operational system wiring in the cabin area. Noise sources considered are RF fields from on board transmitters, precipitation static, induced lightning currents, and induced noise from adjacent wiring. The most significant source is noise coupled to video circuits from associated circuits in common connectors. Video signal crosstalk is the primary cause of steady state interference, and mechanically switched control functions cause the largest induced transients.
Low Noise Signal Processing Technique for Monopulse Pointing of DSN 34-meter Diameter Antennas
This paper describes a 31.8 - 32.3 GHz (Ka-band) monopulse antenna pointing system designed to meet a pointing precision requirement of a mean-radial-error (MRE) less than 1.5 milli-degrees for a 34-meter diameter antenna with a 17 milli-degree 3-dB beam-width, under windy conditions up to 15mph.
The effect of digitizing noise on spectral signal to noise ratios in Fourier spectroscopy
Digitizing noise effects on spectral signal to noise ratio in Fourier spectroscopy
Periodic variations in the signal-to-noise ratios of signals received from the ICE spacecraft
Data from the ICE probe to comet Giacobini-Zinner are analyzed to determine the effects of spacecraft rotation upon the signal to noise ratio (SNR) for the two channels of data. In addition, long-term variations from sources other than rotations are considered. Results include a pronounced SNR variation over a period of three seconds (one rotation) and a lesser effect over a two minute period (possibly due to the receiving antenna conscan).
Effects of transmitted noise on receiver signal-to-noise ratios
Effects of transmitted noise on receiver signal to noise ratios
Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware
This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the noise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.
Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware
This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.
System for Improving Signal-to-noise Ratio of a Communication Signal
This invention relates to a system for use in a ground station radio communication receiver for improving the signal-to-noise ratio of weak signals received from distant spacecraft.