SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Analog circuit is employed to smooth change between levels of quantized voltage signal without adversely affecting its fidelity. Circuit is applicable to units requiring interface between digital and analog systems such as automated manufacturing systems or industrial robots.
Digital filters response errors due to signal amplitude quantization, resulting from analog-to- digital conversion and arithmetic operations
Typically an analog signal from a space system is sampled, quantized by Analog-to-Digital (A/D) conversion, merged into a bit stream, communicated to a ground station, received by the ground station, and processed by the ground station to extract useful information for dissemination to the users. The cost of each of these steps is reduced as the number of quantization steps is reduced in the A/D converter. The number of quantization steps should be as small as possible without losing the required information content. This report deals specifically with the accuracy of averages as a function of the number of quantized samples used to compute the averages with the noise on the analog signal as a parameter. For example, the success of the Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) Demonstration depends upon temporally averaging multiple samples in an effort to reduce noise to a sufficiently low level such that temperature profile sounding is made possible. A tutorial description of this process is presented.
Demonstration that the error signal incurred by block quantizing stationary data is nonstationary under some conditions. Examples are presented which indicate that the mean square error is largest at the block edges. When block quantizers are used to encode pictures at low bit rates, this effect tends to make the block edges visible in the reconstructed picture.
Upper bound determination for errors due to signal quantization in multirate digital control system through state variable or z transform formulations
It is shown that an otherwise stable digital control system can be made unstable by signal quantization when the controller operates on floating-point arithmetic. Sufficient conditions of instability are determined, and an example of loss of stability is treated when only one quantizer is operated.
Algorithm based on dynamic programming developed for specific values of quantizer parameters
The results are reported of research into the effects on system operation of signal quantization in a digital control system. The investigation considered digital controllers (filters) operating in floating-point arithmetic in either open-loop or closed-loop systems. An error analysis technique is developed, and is implemented by a digital computer program that is based on a digital simulation of the system. As an output the program gives the programing form required for minimum system quantization errors (either maximum of rms errors), and the maximum and rms errors that appear in the system output for a given bit configuration. The program can be integrated into existing digital simulations of a system.
Algorithm based on dynamic programming developed for specific values of quantizer parameters
Signal quantization induced low amplitude oscillations in digital control systems, discussing relationship to digital controller programming form
The paper discusses Viking lander cameras which have an angular resolution of 0.12 deg, and (for broadband imaging) a resolution of 0.04 deg, used for the acquisition of data in six spectral bands for color and near-infrared imaging. Attention is given to photogrammetric calibration techniques used in the determination of spatial and spectral brightness variations from image data. The effects of sampling on the achievable photogrammetric precision are described along with techniques for preflight spectral calibrations and the corrections required for degradation in the infrared response of the detectors. The effects of the known internal reflections on the qualitative images (such as the appearance of artifact clouds) are presented, noting their effects on skyline radiometry. The qualitative and quantitative effects of the signal quantization are briefly reviewed.
The feasibility of designing a digital, complex, baseband mixer with a 50 MHz sampling rate is explored. The baseband filter must provide passbands with linear phase response to minimize intersymbol interference. The effects of signal quantization, filter coefficient quantization, dynamic range, filter response characteristics, and the performance of the mixer when used for cross correlation and autocorrelation pulse detection techniques are discussed. This filter was designed for use in the high speed data acquisition system (HSDAS), an advanced experimental system in the Deep Space Network.
The Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) is designed for mapping of the atmospheric ozone distribution. Absorption by sulfur dioxide at the same ultraviolet spectral wavelengths makes it possible to observe and resolve the size of volcanic clouds. The sulfur dioxide absorption is discriminated from ozone and water clouds in the data processing by their spectral signatures. Thus, the sulfur dioxide can serve as a tracer which appears in volcanic eruption clouds because it is not present in other clouds. The detection limit with TOMS is close to the theoretical limit due to telemetry signal quantization of 1000 metric tons (5-sigma threshold) within the instrument field of view (50 by 50 km near the nadir). Requirements concerning the use of TOMS in detection of eruptions, geochemical cycles, and volcanic climatic effects are discussed.
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.
Design of optimum quantizers for quantizer-input message signal and quantizer-input message signal contaminated by noise
Some theoretical and experimental results on optimal sampling and quantization of synthetic aperture radar (SAR) signals are presented. It includes a description of a derived theoretical relationship between the pixel signal to noise ratio of processed SAR images and the number of quantization bits per sampled signal, assuming homogeneous extended targets. With this relationship known, a solution may be realized for the problem of optimal allocation of a fixed data bit-volume (for specified surface area and resolution criterion) between the number of samples and the number of bits per sample. The results indicate that to achieve the best possible image quality for a fixed bit rate and a given resolution criterion, one should quantize individual samples coarsely and thereby maximize the number of multiple looks. The theoretical results are then compared with simulation results obtained by processing aircraft SAR data.
A table look-up algorithm for estimating underlying signal and noise parameters from quantized observables is examined. A general mathematical model is developed, and a look-up table designed specifically for estimating parameters from four-bit quantized data is described. Estimator performance is evaluated both analytically and by means of numerical simulation, and an example is provided to illustrate the use of the look-up table for estimating signal-to-noise ratios commonly encountered in Voyager-type data.
In sampled data digital telemetry systems the signal to noise ratio (SNR) is typically derived as a function of the moments of the digitized input stream (e.g., the receiver output). This analog to digital conversion process is itself an additional noise source known as the quantization noise. Thus a digitally measured SNR will only approximately represent the SNR of the analog input signal. A procedure (Sheppard's corrections) for correcting moments of any order for this quantization effect is presented.