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At least 37 records · Page 2

Wideband Digital Signal Processing Test-Bed for Radiometric RFI Mitigation

Radio Frequency Interference (RFI) is a persistent and growing problem experienced by spaceborne microwave radiometers. Recent missions such as SMOS, SMAP, and GPM have detected RFI in L, C, X, and K bands. To proactively deal with this issue, microwave radiometers must (1) Utilize new algorithms for RFI detection (2) Utilize fast digital back-ends that sample at hundreds of MHz. The wideband digital signal processing testbed (WB-RFI) is a platform that allows rapid development and testing various RFI detection and mitigation algorithms.

Bradley, Damon C.

The discrete prolate spheroidal filter as a digital signal processing tool

The discrete prolate spheriodall (DPS) filter is one of the glass of nonrecursive finite impulse response (FIR) filters. The DPS filter is superior to other filters in this class in that it has maximum energy concentration in the frequency passband and minimum ringing in the time domain. A mathematical development of the DPS filter properties is given, along with information required to construct the filter. The properties of this filter were compared with those of the more commonly used filters of the same class. Use of the DPS filter allows for particularly meaningful statements of data time/frequency resolution cell values. The filter forms an especially useful tool for digital signal processing.

Mathews, J. D.

An evaluation of the Intel 2920 digital signal processing integrated circuit

The circuit consists of a digital to analog converter, accumulator, read write memory and UV erasable read only memory. The circuit can convert an analog signal to a digital representation, perform mathematical operations on the digital signal and subsequently convert the digital signal to an analog output. Development software tailored for programming the 2920 is presented.

Heller, J.

Digital signal processing in the radio science stability analyzer

The Telecommunications Division has built a stability analyzer for testing Deep Space Network installations during flight radio science experiments. The low-frequency part of the analyzer operates by digitizing wave signals with bandwidths between 80 Hz and 45 kHz. Processed outputs include spectra of signal, phase, amplitude, and differential phase; time series of the same quantities; and Allan deviation of phase and differential phase. This article documents the digital signal-processing methods programmed into the analyzer.

Greenhall, C. A.

Implementation of real-time digital signal processing systems

Special purpose hardware implementation of DFT Computers and digital filters is considered in the light of newly introduced algorithms and IC devices. Recent work by Winograd on high-speed convolution techniques for computing short length DFT's, has motivated the development of more efficient algorithms, compared to the FFT, for evaluating the transform of longer sequences. Among these, prime factor algorithms appear suitable for special purpose hardware implementations. Architectural considerations in designing DFT computers based on these algorithms are discussed. With the availability of monolithic multiplier-accumulators, a direct implementation of IIR and FIR filters, using random access memories in place of shift registers, appears attractive. The memory addressing scheme involved in such implementations is discussed. A simple counter set-up to address the data memory in the realization of FIR filters is also described. The combination of a set of simple filters (weighting network) and a DFT computer is shown to realize a bank of uniform bandpass filters. The usefulness of this concept in arriving at a modular design for a million channel spectrum analyzer, based on microprocessors, is discussed.

Narasimha, M.

Rounding Technique for High-Speed Digital Signal Processing

Arithmetic technique facilitates high-speed rounding of 2's complement binary data. Conventional rounding of 2's complement numbers presents problems in high-speed digital circuits. Proposed technique consists of truncating K + 1 bits then attaching bit in least significant position. Mean output error is zero, eliminating introducing voltage offset at input.

Wechsler, E. R.

UCMS - A new signal parameter measurement system using digital signal processing techniques

The User Constraint Measurement System (UCMS) is a hardware/software package developed by NASA Goddard to measure the signal parameter constraints of the user transponder in the TDRSS environment by means of an all-digital signal sampling technique. An account is presently given of the features of UCMS design and of its performance capabilities and applications; attention is given to such important aspects of the system as RF interface parameter definitions, hardware minimization, the emphasis on offline software signal processing, and end-to-end link performance. Applications to the measurement of other signal parameters are also discussed.

Choi, H. J.

Energy shadowing correction of ultrasonic pulse-echo records by digital signal processing

A numerical algorithm is described that enables the correction of energy shadowing during the ultrasonic testing of bulk materials. In the conventional method, an ultrasonic transducer transmits sound waves into a material that is immersed in water so that discontinuities such as defects can be revealed when the waves are reflected and then detected and displayed graphically. Since a defect that lies behind another defect is shadowed in that it receives less energy, the conventional method has a major drawback. The algorithm normalizes the energy of the incoming wave by measuring the energy of the waves reflected off the water/air interface. The algorithm is fast and simple enough to be adopted for real time applications in industry. Images of material defects with the shadowing corrections permit more quantitative interpretation of the material state.

Kishonio, D.

Energy shadowing correction of ultrasonic pulse-echo records by digital signal processing

Attention is given to a numerical algorithm that, via signal processing, enables the dynamic correction of the shadowing effect of reflections on ultrasonic displays. The algorithm was applied to experimental data from graphite-epoxy composite material immersed in a water bath. It is concluded that images of material defects with the shadowing corrections allow for a more quantitative interpretation of the material state. It is noted that the proposed algorithm is fast and simple enough to be adopted for real time applications in industry.

Kishoni, D.

Fault tolerance in space-based digital signal processing and switching systems: Protecting up-link processing resources, demultiplexer, demodulator, and decoder

Fault tolerance features in the first three major subsystems appearing in the next generation of communications satellites are described. These satellites will contain extensive but efficient high-speed processing and switching capabilities to support the low signal strengths associated with very small aperture terminals. The terminals' numerous data channels are combined through frequency division multiplexing (FDM) on the up-links and are protected individually by forward error-correcting (FEC) binary convolutional codes. The front-end processing resources, demultiplexer, demodulators, and FEC decoders extract all data channels which are then switched individually, multiplexed, and remodulated before retransmission to earth terminals through narrow beam spot antennas. Algorithm based fault tolerance (ABFT) techniques, which relate real number parity values with data flows and operations, are used to protect the data processing operations. The additional checking features utilize resources that can be substituted for normal processing elements when resource reconfiguration is required to replace a failed unit.

Redinbo, Robert

Adaptive Noise Suppression Using Digital Signal Processing

A signal to noise ratio dependent adaptive spectral subtraction algorithm is developed to eliminate noise from noise corrupted speech signals. The algorithm determines the signal to noise ratio and adjusts the spectral subtraction proportion appropriately. After spectra subtraction low amplitude signals are squelched. A single microphone is used to obtain both eh noise corrupted speech and the average noise estimate. This is done by determining if the frame of data being sampled is a voiced or unvoiced frame. During unvoice frames an estimate of the noise is obtained. A running average of the noise is used to approximate the expected value of the noise. Applications include the emergency egress vehicle and the crawler transporter.

Kozel, David

Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform

Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged digital quantum resources, such as discrete-variable (DV) systems like qubits, rather than analog quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals—specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.

42 ENGINEERING

Input-output characterization of an ultrasonic testing system by digital signal analysis

The input/output characteristics of an ultrasonic testing system used for stress wave factor measurements were studied. The fundamentals of digital signal processing are summarized. The inputs and outputs are digitized and processed in a microcomputer using digital signal processing techniques. The entire ultrasonic test system, including transducers and all electronic components, is modeled as a discrete-time linear shift-invariant system. Then the impulse response and frequency response of the continuous time ultrasonic test system are estimated by interpolating the defining points in the unit sample response and frequency response of the discrete time system. It is found that the ultrasonic test system behaves as a linear phase bandpass filter. Good results were obtained for rectangular pulse inputs of various amplitudes and durations and for tone burst inputs whose center frequencies are within the passband of the test system and for single cycle inputs of various amplitudes. The input/output limits on the linearity of the system are determined.

Karaguelle, H.

Input-output characterization of an ultrasonic testing system by digital signal analysis

Ultrasonic test system input-output characteristics were investigated by directly coupling the transmitting and receiving transducers face to face without a test specimen. Some of the fundamentals of digital signal processing were summarized. Input and output signals were digitized by using a digital oscilloscope, and the digitized data were processed in a microcomputer by using digital signal-processing techniques. The continuous-time test system was modeled as a discrete-time, linear, shift-invariant system. In estimating the unit-sample response and frequency response of the discrete-time system, it was necessary to use digital filtering to remove low-amplitude noise, which interfered with deconvolution calculations. A digital bandpass filter constructed with the assistance of a Blackman window and a rectangular time window were used. Approximations of the impulse response and the frequency response of the continuous-time test system were obtained by linearly interpolating the defining points of the unit-sample response and the frequency response of the discrete-time system. The test system behaved as a linear-phase bandpass filter in the frequency range 0.6 to 2.3 MHz. These frequencies were selected in accordance with the criterion that they were 6 dB below the maximum peak of the amplitude of the frequency response. The output of the system to various inputs was predicted and the results were compared with the corresponding measurements on the system.

Williams, J. H., Jr.

Fourier analysis and signal processing by use of the Moebius inversion formula

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.

Reed, Irving S.