The distribution of the outputs from a filter band signal processing system
Distribution of outputs from filter band signal processing system
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Distribution of outputs from filter band signal processing system
This study analyzes the effect of signal processing variables on the ability of the ultrasonic guided wave scan method at NASA Glenn Research Center to distinguish various flaw conditions in ceramic matrix composites samples. In the ultrasonic guided wave scan method, several time- and frequency-domain parameters are calculated from the ultrasonic guided wave signal at each scan location to form images. The parameters include power spectral density, centroid mean time, total energy (zeroth moment), centroid frequency, and ultrasonic decay rate. A number of signal processing variables are available to the user when calculating these parameters. These signal processing variables include 1) the time portion of the time-domain waveform processed, 2) integration type for the properties requiring integrations, 3) bounded versus unbounded integrations, 4) power spectral density window type, 5) and the number of time segments chosen if using the short-time fourier transform to calculate ultrasonic decay rate. Flaw conditions examined included delamination, cracking, and density variation.
This report presents the research, design, and implementation of a Toroid Signal Processing Container with Redis Integration, conducted during my internship assignment. The project focused on developing a modular signal processing sys- tem capable of performing baseline correction, droop compensation, and real- time data communication for beam diagnostic signals. Using Redis as a message broker and configuration manager, the system ensures modularity, scalability, and efficient inter-process communication. Signal correction algorithms, such as Asymmetric Least Squares (ALS) baseline smoothing and a numerical droop correction approach, were implemented and tested using Linac beam data. The results confirm that this system improves signal fidelity and supports real-time analysis requirements, offering valuable contributions to the field of beam instrumentation and data acquisition systems.
This report presents the research, design, and implementation of a Toroid Signal Processing Container with Redis Integration, conducted during my internship assignment. The project focused on developing a modular signal processing sys- tem capable of performing baseline correction, droop compensation, and real- time data communication for beam diagnostic signals. Using Redis as a message broker and configuration manager, the system ensures modularity, scalability, and efficient inter-process communication. Signal correction algorithms, such as Asymmetric Least Squares (ALS) baseline smoothing and a numerical droop correction approach, were implemented and tested using Linac beam data. The results confirm that this system improves signal fidelity and supports real-time analysis requirements, offering valuable contributions to the field of beam in- strumentation and data acquisition systems.
Over the past year, two Rogue GPS prototype receivers have been assembled and successfully subjected to a variety of laboratory and field tests. A functional description is presented of signal processing in the Rogue receiver, tracing the signal from RF input to the output values of group delay, phase, and data bits. The receiver can track up to eight satellites, without time multiplexing among satellites or channels, simultaneously measuring both group delay and phase for each of three channels (L1-C/A, L1-P, L2-P). The Rogue signal processing described requires generation of the code for all three channels. Receiver functional design, which emphasized accuracy, reliability, flexibility, and dynamic capability, is summarized. A detailed functional description of signal processing is presented, including C/A-channel and P-channel processing, carrier-aided averaging of group delays, checks for cycle slips, acquistion, and distinctive features.
The laser Doppler velocimeter system (LDV) being tested at NASA MSFC, Alabama, relies on a bank of classical filters for processing the returned lidar signal. Due to the complexity of this conventional filter system, alternative signal processing methods have been proposed for obtaining the Doppler spectrum. The fast Fourier transform (FFT) and the pulse-pair estimator are two techniques which appear to offer some advantages over the existing system. The work reported employs digital computer simulation to compare and evaluate these two processing methods for determining the first and second moments of the LDV velocity spectrum.
This paper describes the implementation of a Digital Signal Processing (DP) subsystem for a single Long Wavelength Array (LWA) station.12 The LWA is a radio telescope that will consist of many phased array stations. Each LWA station consists of 256 pairs of dipole-like antennas operating over the 10-88 MHz frequency range. The Digital Signal Processing subsystem digitizes up to 260 dual-polarization signals at 196 MHz from the LWA Analog Receiver, adjusts the delay and amplitude of each signal, and forms four independent beams. Coarse delay is implemented using a first-in-first-out buffer and fine delay is implemented using a finite impulse response filter. Amplitude adjustment and polarization corrections are implemented using a 2x2 matrix multiplication
Four tasks related to the signal processing aspects of the severe-storms Doppler lidar program are discussed. The development of algorithms for windfield retrieval from Doppler lidar measurements are discussed. Signal processor installation on a CV-990 aircraft is discussed.
A communication satellite with a multiple-beam antenna and onboard signal processing is considered for use in a 'message-switched' data relay system. The signal processor may incorporate demodulation, routing, storage, and remodulation of the data. A system user model is established and key functional elements for the signal processing are identified. With the throughput and delay requirements as the controlled variables, the hardware complexity, operational discipline, occupied bandwidth, and overall user end-to-end cost are estimated for (1) random-access packet switching; and (2) reservation-access packet switching. Other aspects of this network (eg, the adaptability to channel switched traffic requirements) are examined. For the given requirements and constraints, the reservation system appears to be the most attractive protocol.
Signal-processing theory for the TurboRogue receiver is presented. The signal form is traced from its formation at the GPS satellite, to the receiver antenna, and then through the various stages of the receiver, including extraction of phase and delay. The analysis treats the effects of ionosphere, troposphere, signal quantization, receiver components, and system noise, covering processing in both the 'code mode' when the P code is not encrypted and in the 'P-codeless mode' when the P code is encrypted. As a possible future improvement to the current analog front end, an example of a highly digital front end is analyzed.
Signal processing in satellite radar altimeter model above geoid
Analog modulation, frequency-division multiplexing and signal processing for multiple-access satellite communication
An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.
We investigate a deep learning-based signal processing for liquid argon time projection chambers (LArTPCs), a leading detector technology in neutrino physics. Identifying regions of interest (ROIs) in LArTPCs is challenging due to signal cancellation from bipolar responses and various detector effects observed in real data. We approach ROI identification as an image segmentation task, and employ a U-ResNet architecture. The network is trained on samples that incorporate detector geometry information and include a range of detector variations. Our approach significantly outperforms traditional methods while maintaining robustness across diverse detector conditions. This method has been adopted for signal processing in the Short-Baseline Neutrino program and provides a valuable foundation for future experiments such as the Deep Underground Neutrino Experiment.
A novel Fourier technique for digital signal processing is developed. This approach to Fourier analysis is based on the number-theoretic method of the Moebius inversion of series. The Fourier transform method developed is shown also to yield the convolution of two signals. A computer simulation shows that this method for finding Fourier coefficients is quite suitable for digital signal processing. It competes with the classical FFT (fast Fourier transform) approach in terms of accuracy, complexity, and speed.
Multiple access techniques for communications satellites - digital modulation, time division multiplexing, and related signal processing
A microprocessor based digital signal processing unit has been proposed to replace analog sections of a microwave radiometer. A brief introduction to the radiometer system involved and a description of problems encountered in the use of digital techniques in radiometer design are discussed. An analysis of the digital signal processor as part of the radiometer is then presented.
Analysis and definition of digital techniques for signal processing