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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The Digital Data Acquisition System for the Russian VLBI Network of New Generation

The system consists of several identical channels of 1024 MHz bandwidth each. In each channel, the RF band is frequency-translated to the intermediate frequency range 1 - 2 GHz. Each channel consists of two parts: the digitizer and Mark 5C recorder. The digitizer is placed on the antenna close to the corresponding Low-Noise Amplifier output and consists of the analog frequency converter, ADC, and a device for digital processing of the signals using FPGA. In the digitizer the subdigitization on frequency of 2048 MHz is used. For producing narrow-band channels and to interface with existing data acquisition systems, the polyphase filtering with FPGA can be used. Digital signals are re-quantized to 2-bits in the FPGA and are transferred to an input of Mark 5C through a fiber line. The breadboard model of the digitizer is being tested, and the data acquisition system is being designed.

Fedotov, Leonid↗
NASA NTRS1979

Some effects of quantization on a noiseless phase-locked loop

If the VCO of a phase-locked receiver is to be replaced by a digitally programmed synthesizer, the phase error signal must be sampled and quantized. Effects of quantizing after the loop filter (frequency quantization) or before (phase error quantization) are investigated. Constant Doppler or Doppler rate noiseless inputs are assumed. The main result gives the phase jitter due to frequency quantization for a Doppler-rate input. By itself, however, frequency quantization is impractical because it makes the loop dynamic range too small.

Greenhall, C. A.↗
NASA NTRS2014

Design and Development of the SMAP Microwave Radiometer Electronics

The SMAP microwave radiometer will measure land surface brightness temperature at L-band (1413 MHz) in the presence of radio frequency interference (RFI) for soil moisture remote sensing. The radiometer design was driven by the requirements to incorporate internal calibration, to operate synchronously with the SMAP radar, and to mitigate the deleterious effects of RFI. The system design includes a highly linear super-heterodyne microwave receiver with internal reference loads and noise sources for calibration and an innovative digital signal processor and detection system. The front-end comprises a coaxial cable-based feed network, with a pair of diplexers and a coupled noise source, and radiometer front-end (RFE) box. Internal calibration is provided by reference switches and a common noise source inside the RFE. The RF back-end (RBE) downconverts the 1413 MHz channel to an intermediate frequency (IF) of 120 MHz. The IF signals are then sampled and quantized by high-speed analog-to-digital converters in the radiometer digital electronics (RDE) box. The RBE local oscillator and RDE sampling clocks are phase-locked to a common reference to ensure coherency between the signals. The RDE performs additional filtering, sub-band channelization, cross-correlation for measuring third and fourth Stokes parameters, and detection and integration of the first four raw moments of the signals. These data are packetized and sent to the ground for calibration and further processing. Here we discuss the novel features of the radiometer hardware particularly those influenced by the need to mitigate RFI.

radio frequency interference↗
NASA NTRS1972

Quantization noise in digital speech

The amount of quantization noise generated in a digital-to-analog converter is dependent on the number of bits or quantization levels used to digitize the analog signal in the analog-to-digital converter. The minimum number of quantization levels and the minimum sample rate were derived for a digital voice channel. A sample rate of 6000 samples per second and lowpass filters with a 3 db cutoff of 2400 Hz are required for 100 percent sentence intelligibility. Consonant sounds are the first speech components to be degraded by quantization noise. A compression amplifier can be used to increase the weighting of the consonant sound amplitudes in the analog-to-digital converter. An expansion network must be installed at the output of the digital-to-analog converter to restore the original weighting of the consonant sounds. This technique results in 100 percent sentence intelligibility for a sample rate of 5000 samples per second, eight quantization levels, and lowpass filters with a 3 db cutoff of 2000 Hz.

Schmidt, O. L.↗
NASA NTRS1990

Real-time data compression of broadcast video signals

A non-adaptive predictor, a nonuniform quantizer, and a multi-level Huffman coder are incorporated into a differential pulse code modulation system for coding and decoding broadcast video signals in real time.

Shalkhauser, Mary J.↗
NASA NTRS1991

Real-time data compression of broadcast video signals

A non-adaptive predictor, a nonuniform quantizer, and a multi-level Huffman coder are incorporated into a differential pulse code modulation system for coding and decoding broadcast video signals in real time.

Shalkauser, Mary Jo W.↗
NASA NTRS1975

Formulation of the information capacity of the optical-mechanical line-scan imaging process

An expression for the information capacity of the optical-mechanical line-scan imaging process is derived which includes the effects of blurring of spatial, photosensor noise, aliasing, and quantization. Both the information capacity for a fixed data density and the information efficiency (the ratio of information capacity to data density) exhibit a distinct single maximum when displayed as a function of sampling rate, and the location of this maximum was determined by the system frequency-response shape, signal-to-noise ratio, and quantization interval.

Huck, F. O.↗
NASA NTRS1976

Evaluation of NASA speech encoder

Techniques developed by NASA for spaceflight instrumentation were used in the design of a quantizer for speech-decoding. Computer simulation of the actions of the quantizer was tested with synthesized and real speech signals. Results were evaluated by a phometician. Topics discussed include the relationship between the number of quantizer levels and the required sampling rate; reconstruction of signals; digital filtering; speech recording, sampling, and storage, and processing results.

Source record↗
NASA NTRS1973

Transmission of radiometer data from the Synchronous Meteorological Satellite

The Synchronous Meteorological Satellite uses a spin scanner radiometer which generates eight visual signals and two infrared signals. These signals are multiplexed and converted into a 28-Mbps data stream. This signal is transmitted to ground by quadriphase modulation at 1686.1 MHz. On the ground, the digital signal is reconstructed to an analog signal. To conserve bandwidth, an analog-to-digital converter with a nonlinear transfer function was used for the visual signals. The size of the quantization step was made proportional to the noise output of the scanner photomultiplier tube which increases as the square root of incident light. The radiometer data transmission link was simulated on a digital computer to determine the transfer function. Some results of the simulation are shown.

Davies, R. S.↗
NASA NTRS1992

Spatially-varying IIR filter banks for image coding

This paper reports on the application of spatially variant infinite impulse response (IIR) filter banks to subband image coding. The new filter bank is based on computationally efficient recursive polyphase decompositions that dynamically change in response to the input signal. In the absence of quantization, reconstruction can be made exact. However, by proper choice of an adaptation scheme, we show that subband image coding based on time varying filter banks can yield improvement over the use of conventional filter banks.

Chung, Wilson C.↗
NASA NTRS1982

A discussion of image sharpness

The image sharpness problem is discussed in terms of a scene which is viewed by a sensor. The sensor has some sort of function which is a nonpoint observing function, and it's a function that gathers energy from some region around a point in the scene. That energy is integrated and is contributed to each point or each sample that is taken of the scene. The samples become the pixels, and the pixels are assembled together into the digital image. Each one has some blurr or some of what is called the point's spread function creating the value of information or data that is seen in each pixel. Then the sensor and electronic part of the system acts on that signal out of the sensor and perhaps adds more blurring, more loss of resolution to the system. Finally, sampling and quantization of the data produce their effects. The signal is sampled at some rate and the digital image is created from that. The sampling or digitizing process puts the continuous voltage into a number of discrete binary levels, and another error is introduced there.

Anuta, P.↗
NASA NTRS1994

On the application of under-decimated filter banks

Maximally decimated filter banks have been extensively studied in the past. A filter bank is said to be under-decimated if the number of channels is more than the decimation ratio in the subbands. A maximally decimated filter bank is well known for its application in subband coding. Another application of maximally decimated filter banks is in block filtering. Convolution through block filtering has the advantages that parallelism is increased and data are processed at a lower rate. However, the computational complexity is comparable to that of direct convolution. More recently, another type of filter bank convolver has been developed. In this scheme, the convolution is performed in the subbands. Quantization and bit allocation of subband signals are based on signal variance, as in subband coding. Consequently, for a fixed rate, the result of convolution is more accurate than is direct convolution. This type of filter bank convolver also enjoys the advantages of block filtering, parallelism, and a lower working rate. Nevertheless, like block filtering, there is no computational saving. In this article, under-decimated systems are introduced to solve the problem. The new system is decimated only by half the number of channels. Two types of filter banks can be used in the under-decimated system: the discrete Fourier transform (DFT) filter banks and the cosine modulated filter banks. They are well known for their low complexity. In both cases, the system is approximately alias free, and the overall response is equivalent to a tunable multilevel filter. Properties of the DFT filter banks and the cosine modulated filter banks can be exploited to simultaneously achieve parallelism, computational saving, and a lower working rate. Furthermore, for both systems, the implementation cost of the analysis or synthesis bank is comparable to that of one prototype filter plus some low-complexity modulation matrices. The individual analysis and synthesis filters have complex coefficients in the DFT filter banks but have real coefficients in the cosine modulated filter banks.

Lin, Y.-P.↗
NASA NTRS2002

Remote Sensing Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properties such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization and band-to-band registration drive sensor platform and spacecraft system architecture and cost, analysis of these criteria is important to optimize system design objectively. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy and geopositional accuracy affect the complexity and cost of calibration methods. However, few studies have quantified the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at the John C. Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated datasets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood.

Zanoni, Vicki↗
NASA NTRS2002

Remote Sensing System Requirements Development: A Simulation-Based Approach

Earth science research and application requirements for multispectral data have often been driven by currently available remote sensing technology. Few parametric studies exist that specify data required for certain applications. Consequently, data requirements are often defined based on the best data available or on what has worked successfully in the past. Since properites such as spatial resolution, swath width, spectral bands, signal-to-noise ratio (SNR), data quantization, and band-to-band registration drive sensor platform and spaceraft system architecture and cost, analysis of these criteria is important to objectively optimize system design. Remote sensing data requirements are also linked to calibration and characterization methods. Parameters such as spatial resolution, radiometric accuracy, and geopositional accuracy affect the complexity and cost of calibration methods. However, there are few studies that quantify the true accuracies required for specific problems. As calibration methods and standards are proposed, it is important that they be tied to well-known data requirements. The Application Research Toolbox (ART) developed at Stennis Space Center provides a simulation-based method for multispectral data requirements development. The ART produces simulated data sets from hyperspectral data through band synthesis. Parameters such as spectral band shape and width, SNR, data quantization, spatial resolution, and band-to-band registration can be varied to create many different simulated data products. Simulated data utility can then be assessed for different applications so that requirements can be better understood. This paper describes the ART and its applicability for rigorously deriving remote sensing data requirements.

Zanoni, Vicki↗
NASA NTRS1993

Applications of wavelet-based compression to multidimensional Earth science data

A data compression algorithm involving vector quantization (VQ) and the discrete wavelet transform (DWT) is applied to two different types of multidimensional digital earth-science data. The algorithms (WVQ) is optimized for each particular application through an optimization procedure that assigns VQ parameters to the wavelet transform subbands subject to constraints on compression ratio and encoding complexity. Preliminary results of compressing global ocean model data generated on a Thinking Machines CM-200 supercomputer are presented. The WVQ scheme is used in both a predictive and nonpredictive mode. Parameters generated by the optimization algorithm are reported, as are signal-to-noise (SNR) measurements of actual quantized data. The problem of extrapolating hydrodynamic variables across the continental landmasses in order to compute the DWT on a rectangular grid is discussed. Results are also presented for compressing Landsat TM 7-band data using the WVQ scheme. The formulation of the optimization problem is presented along with SNR measurements of actual quantized data. Postprocessing applications are considered in which the seven spectral bands are clustered into 256 clusters using a k-means algorithm and analyzed using the Los Alamos multispectral data analysis program, SPECTRUM, both before and after being compressed using the WVQ program.

Bradley, Jonathan N.↗
NASA NTRS1991

Improvement in detection of small wildfires

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

Sleigh, William J.↗