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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.
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Properties of The RFI Environment at 1400-1427 MHz as observed by the Soil Moisture Active/Passive Mission Microwave Radiometer
The soil moisture active/passive (SMAP) satellite microwave radiometer has been providing global measurements of L-band thermal emission from Earth since April 2015. Although the radiometer operates in the protected 1400–1427 MHz portion of the radio spectrum, its measurements are still corrupted by either radio frequency interference (RFI) from out-of-band emissions via legal sources or by sources operating in-band illegally. The SMAP radiometer includes a digital backend that enables implementation of multiple ground-based RFI detection and filtering algorithms. This data is used to collect statistics and trends of Earth's RFI environment. This article examines properties of the global RFI environment as observed by SMAP, including information on RFI source properties (obtained from analysis of SMAP multiple detector outputs) and the evolution of the RFI environment in time. Residual RFI contributions after the application of SMAP RFI processing are also examined as preliminary information for the development of future methods to address their effect.
A Simulation-based Method for Correcting Mode Coupling in CMB Angular Power Spectra
Modern cosmic microwave background (CMB) analysis pipelines regularly employ complex time-domain filters, beam models, masking, and other techniques during the production of sky maps and their corresponding angular power spectra. However, these processes can generate couplings between multipoles from the same spectrum and from different spectra, in addition to the typical power attenuation. Within the context of pseudo-C ℓ based, MASTER-style analyses, the net effect of the time-domain filtering is commonly approximated by a multiplicative transfer function, F ℓ , that can fail to capture mode mixing and is dependent on the spectrum of the signal. To address these shortcomings, we have developed a simulation-based spectral correction approach that constructs a two-dimensional transfer matrix, ${J}_{{\ell }{\ell }^{\prime} }$, which contains information about mode mixing in addition to mode attenuation. We demonstrate the application of this approach on data from the first flight of the Spider balloon-borne CMB experiment.
Linear minimum variance filters applied to carrier tracking
A new approach is taken to the problem of tracking a fixed amplitude signal with a Brownian-motion phase process. Classically, a first-order phase-lock loop (PLL) is used; here, the problem is treated via estimation of the quadrature signal components. In this space, the state dynamics are linear with white multiplicative noise. Therefore, linear minimum-variance filters, which have a particularly simple mechanization, are suggested. The resulting error dynamics are linear at any signal/noise ratio, unlike the classical PLL. During synchronization, and above threshold, this filter with constant gains degrades by 3 per cent in output rms phase error with respect to the classical loop. However, up to 80 per cent of the maximum possible noise improvement is obtained below threshold, where the classical loop is nonoptimum, as demonstrated by a Monte Carlo analysis. Filter mechanizations are presented for both carrier and baseband operation.
Autocorrelation peaks in congruential pseudorandom number generators
The complete correlation structure of several congruential pseudorandom number generators (PRNG) of the same type and small cycle length was studied to deal with the problem of congruential PRNG almost repeating themselves at intervals smaller than their cycle lengths, during simulation of bandpass filtered normal random noise. Maximum period multiplicative and mixed congruential generators were studied, with inferences drawn from examination of several tractable members of a class of random number generators, and moduli from 2 to the 5th power to 2 to the 9th power. High correlation is shown to exist in mixed and multiplicative congruential random number generators and prime moduli Lehmer generators for shifts a fraction of their cycle length. The random noise sequences in question are required when simulating electrical noise, air turbulence, or time variation of wind parameters.
Retrieval of Aerosol Properties from Multi-Spectral Extinction Measurements
The direct-beam spectral extinction of solar radiation contains information on atmospheric composition in a form that is essentially free from the data analysis complexities that often arise from multiple scattering. Ground based Multi-Filter Shadowband Radiometer (MFRSR) measurements provide such information for the vertical atmospheric column path, while solar occultation measurements from a satellite platform provide horizontal slices through the atmosphere. We describe application of a Multi-Spectral Atmospheric Column Extinction (MACE) analysis technique used to analyze MFRSR data also to occultation measurements made by SAGE II. For analysis, we select the 1985 Nevado del Ruiz volcanic eruption period to retrieve atmospheric profiles of ozone and NO2, and changes in the stratospheric aerosol size and optical depth. The time evolution of volcanic aerosol serves as a passive tracer to study stratospheric dynamics, and changes in particle size put constraints on the sulfur chemistry modeling of volcanic aerosols. Paper presented at The '99 Kyoto Aerosol-Cloud Workshop, held Dec 1-3, 1999, Kyoto, Japan
Retrieval of Aerosol Properties from Multi-Spectral Extinction Measurements
The direct-beam spectral extinction of solar radiation contains information on atmospheric composition in a form that is essentially free from the data analysis complexities that often arise from multiple scattering. Ground based Multi-Filter Shadowband Radiometer (MFRSR) measurements provide such information for the vertical atmospheric column path, while solar occultation measurements from a satellite platform provide horizontal slices through the atmosphere. We describe application of a Multi-Spectral Atmospheric Column Extinction (MACE) analysis technique used to analyze MFRSR data also to occultation measurements made by SAGE 11. For analysis, we select the 1985 Nevado del Ruiz volcanic eruption period to retrieve atmospheric profiles of ozone and NO2, and changes in the stratospheric aerosol size and optical depth. The time evolution of volcanic aerosol serves as a passive tracer to study stratospheric dynamics, and changes in particle size put constraints on the sulfur chemistry modeling of volcanic aerosols.
A comparison of Image Quality Models and Metrics Predicting Object Detection
Many models and metrics for image quality predict image discriminability, the visibility of the difference between a pair of images. Some image quality applications, such as the quality of imaging radar displays, are concerned with object detection and recognition. Object detection involves looking for one of a large set of object sub-images in a large set of background images and has been approached from this general point of view. We find that discrimination models and metrics can predict the relative detectability of objects in different images, suggesting that these simpler models may be useful in some object detection and recognition applications. Here we compare three alternative measures of image discrimination, a multiple frequency channel model, a single filter model, and RMS error.
Reconfigurable Advanced Receiver Design and Implementation
While the demand for real-time broadband information access has grown and continues to grow at a rapid Pace, the need for a reconfigurable receiver system has increased. To achieve the goal to communicate with multiple shuttles at a time, a filter bank in polyphase structure is introduced. This paper presents the design and implementation for high-speed, high-performance, and fixed-point polyphase filter banks. The polyphase filter structure is designed such that the use of a fixed-point system has minimum impact on the performance of the filter. The final hardware implementation is done on a Xilinx FPGA chip.
Hyperspectral Imager-Tracker
The Hyperspectral Imager-Tracker (HIT) is a technique for visualization and tracking of low-contrast, fast-moving objects. The HIT architecture is based on an innovative and only recently developed concept in imaging optics. This innovative architecture will give the Light Prescriptions Innovators (LPI) HIT the possibility of simultaneously collecting the spectral band images (hyperspectral cube), IR images, and to operate with high-light-gathering power and high magnification for multiple fast- moving objects. Adaptive Spectral Filtering algorithms will efficiently increase the contrast of low-contrast scenes. The most hazardous parts of a space mission are the first stage of a launch and the last 10 kilometers of the landing trajectory. In general, a close watch on spacecraft operation is required at distances up to 70 km. Tracking at such distances is usually associated with the use of radar, but its milliradian angular resolution translates to 100- m spatial resolution at 70-km distance. With sufficient power, radar can track a spacecraft as a whole object, but will not provide detail in the case of an accident, particularly for small debris in the onemeter range, which can only be achieved optically. It will be important to track the debris, which could disintegrate further into more debris, all the way to the ground. Such fragmentation could cause ballistic predictions, based on observations using high-resolution but narrow-field optics for only the first few seconds of the event, to be inaccurate. No optical imager architecture exists to satisfy NASA requirements. The HIT was developed for space vehicle tracking, in-flight inspection, and in the case of an accident, a detailed recording of the event. The system is a combination of five subsystems: (1) a roving fovea telescope with a wide 30 field of regard; (2) narrow, high-resolution fovea field optics; (3) a Coude optics system for telescope output beam stabilization; (4) a hyperspectral-mutispectral imaging assembly; and (5) image analysis software with effective adaptive spectral filtering algorithm for real-time contrast enhancement.
Phase-change Tunable Filters (PCTFs) for Hyperspectral Thermal Imaging
In this presentation, we introduce phase-change tunable filters (PCTFs), which are capable of actively tunable spectral filtering as well as continuous tuning (hyperspectral) across multiple IR wavebands (1–10 μm); several orders-of-magnitude faster switching speeds (GHz–MHz) than the state-of-the-art, and narrowband filtering (~50 nm passband). This technology subsystem is based on the unique electro-optics of non-volatile, phase-change materials (PCMs) such as GeSbTe and SbS. PCMs exhibit a large, reversible refractive index shift through applied energetic pulses. By integrating PCMs with established optical filter designs—whose optical properties are strongly dependent on the constituent materials’ refractive indices—we can rapidly and reversibly tune the PCTFs center wavelength (passband).
Multiple Damage Progression Paths in Model-Based Prognostics
Model-based prognostics approaches employ domain knowledge about a system, its components, and how they fail through the use of physics-based models. Component wear is driven by several different degradation phenomena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics methodology using particle filters, in which the problem of characterizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is represented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model-based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active
Using Fractional Clock-Period Delays in Telemetry Arraying
A set of special digital all-pass finite-impulse- response (FIR) filters produces phase shifts equivalent to delays that equal fractions of the sampling or clock period of a telemetry-data-processing system. These filters have been used to enhance the arraying of telemetry signals that have been received at multiple ground stations from spacecraft (see figure). Somewhat more specifically, these filters have been used to align, in the time domain, the telemetry-data sequences received by the various antennas, in order to maximize the signal-to-noise ratio of the composite telemetric signal obtained by summing the signals received by the antennas. The term arraying in this context denotes a method of enhanced reception of telemetry signals in which several antennas are used to track a single spacecraft. Each antenna receives a signal that comprises a sum of telemetry data plus noise, and these sum data are sent to an arraying combiner for processing. Correlation is the means used to align the set of data from one antenna with that from another antenna. After the data from all the antennas have been aligned in the time domain, they are all added together, sample by sample.
Data Fusion of In-Flight Aerothermodynamic Heating Measurements Using Kalman Filtering
On February 18th, 2021, the Mars 2020 entry system successfully delivered the Perseverance rover to the surface of Mars at Jezero Crater. The entry capsule carried instrumentation installed on the heatshield and backshell, named the Mars Entry, Descent, and Landing Instrumentation 2. The instruments included pressure transducers, thermocouples, heat flux gauges, and a radiometer to measure the aerodynamic and aerothermodynamic performance of the entry vehicle. Three of these sensors, a thermocouple plug, heat flux gauge, and a radiometer, were co-located on the backshell. The sensors were exposed to roughly the same aerodynamic heating, but measured these environments in different ways, each with its own set of modeling and measurement error complications. This paper develops a method for blending each of these measurements together in a single algorithm to produce estimates of the aerothermodynamic environments at that backshell location. The approach makes use of the Kalman-Schmidt filter/smoother methodology, where systematic measurement error parameters are modeled as multiplicative states that are estimated by the filter along with the aerothermal states. The results indicate peak convective and radiative heating values of 0.86 and 5.16 W/cm2, respectively, compared to the filter predictive model values of 0.67 and 4.83 W/cm2.
Data Fusion of In-Flight Aerothermodynamic Heating Measurements Using Kalman Filtering
On February 18th, 2021, the Mars 2020 entry system successfully delivered the Perseverance rover to the surface of Mars at Jezero Crater. The entry capsule carried instrumentation installed on the heatshield and backshell, named the Mars Entry, Descent, and Landing Instrumentation 2. The instruments included pressure transducers, thermocouples, heat flux gauges, and a radiometer to measure the aerodynamic and aerothermodynamic performance of the entry vehicle. Three of these sensors, a thermocouple plug, heat flux gauge, and a radiometer, were co-located on the backshell. The sensors were exposed to roughly the same aerodynamic heating, but measured these environments in different ways, each with its own set of modeling and measurement error complications. This paper develops a method for blending each of these measurements together in a single algorithm to produce estimates of the aerothermodynamic environments at that backshell location. The approach makes use of the Kalman-Schmidt filter/smoother methodology, where systematic measurement error parameters are modeled as multiplicative states that are estimated by the filter along with the aerothermal states. The results indicate peak convective and radiative heating values of 0.86 and 5.16 W/cm$^2$, respectively, compared to the filter predictive model values of 0.67 and 4.83 W/cm$^2$.
Automatic gain-balancing circuit
Energy reaching sensor is collected by telescope, modulated by chopper, spectrally filtered, and simultaneously directed onto two detectors. Gains through multiple signal paths are automatically balanced to 1 part in 10,000. Circuit compensates for slow changes in optical and electrical gains common to gas-filter correlation spectrometers.
Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar
This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.
Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products
Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.