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NASA NTRS2003

Self-Consistent Model of Magnetospheric Ring Current and Electromagnetic Ion Cyclotron Waves: The May 2-7, 1998, Storm

Complete description of a self-consistent model for magnetospheric ring current interacting with electromagnetic ion cyclotron waves is presented. The model is based on the system of two kinetic equations; one equation describes the ring current ion dynamics, and another equation describes the wave evolution. The effects on ring current ions interacting with electromagnetic ion cyclotron waves, and back on waves, are considered self-consistently by solving both equations on a global magnetospheric scale under non steady-state conditions. In the paper by Khazanov et al. [2002] this self-consistent model has only been shortly outlined, and discussions of many the model related details have been omitted. For example, in present study for the first time a new algorithm for numerical finding of the resonant numbers for quasilinear wave-particle interaction is described, or it is demonstrated that in order to describe quasilinear interaction in a multi-ion thermal plasma correctly, both e and He(+) modes of electromagnetic ion cyclotron waves should be employed. The developed model is used to simulate the entire May 2-7, 1998 storm period. Trapped number fluxes of the ring current protons are calculated and presented along with their comparison with the data measured by the 3D hot plasma instrument Polar/HYDRA. Examining of the wave (MLT, L shell) distributions produced during the storm progress reveals an essential intensification of the wave emissions in about two days after main phase of storm. This result is well consistent with the earlier ground-based observations. Also the theoretical shapes and the occurrence rates for power spectral densities of electromagnetic ion cyclotron waves are studied. It is found that in about 2 days after the storm main phase on May 4, mainly non Gaussian shapes of power spectral densities are produced.

Khazanov, G. V.↗

NASA NTRS1977

The low-latitude circulation of Mars

A steady-state two-layer atmospheric model is used in an attempt to simulate the circulation of the equatorial regions of Mars, with consideration of both thermal and mechanical orographic effects. A steady-state solution is sought with the aim of producing mean seasonal circulations upon which tides can be superimposed, and the relative importance of orographic forcing at low latitudes is evaluated. It is assumed that the atmospheres over a topographic feature and over flat terrain possess the same radiative and convective properties, simple dissipation laws are introduced which represent a surface drag effect, and six first-order difference equations are obtained and then reduced to two linear complex second-order coupled difference equations. Analysis of the response of the equinoctial basic wind field to a Gaussian orographic feature situated at the equator and zero deg longitude reveals a number of similarities and differences between the Martian and terrestrial responses. Most of the similarities are explained in terms of the dynamics of a rotating atmosphere, while the major differences are at least partially explained by the different optical properties, lower boundaries, and smaller mass of the Martian atmosphere.

Webster, P. J.↗

NASA NTRSDate not supplied

Estimation With Range Dependent Sensor Model

This paper focuses on the improvement of target tracking accuracy taking into account the sensor’s reading degradation as the relative range increases. The approach is based on the assumption that range measurement error depends on the actual range. Specifically, we model the measurement error as a proportional to the actual range term plus a zero-mean, Gaussian distributed, and uncorrelated process. We present two approaches to tracking a target with constant velocity model. The first approach uses Extended Kalman Filter (EKF) framework to estimate target's states and the unknown proportionality coefficient with linearization on the observation model on the predicted states at each time step. The second one uses a measurement conversion method to estimate the target's scaled by the unknown constant term states, which is shown to be unbiased. This conversion results in linear state and observation models, hence the standard Kalman filter can be applied. The actual target state is computed by application of back scaling with the estimate of unknown scale factor. We evaluate the approaches in desktop simulations.

Target tracking↗

NASA NTRS1993

A simulation study of the performance of the NASA (2,1,6) convolutional code on RFI/burst channels

In an earlier report, the LINKABIT Corporation studied the performance of the (2,1,6) convolutional code on the radio frequency interference (RFI)/burst channel using analytical methods. Using an R(sub 0) analysis, the report concluded that channel interleaving was essential to achieving reliable performance. In this report, Monte Carlo simulation techniques are used to study the performance of the convolutional code on the RFI/burst channel in more depth. The basic system model under consideration is shown. The convolutional code is the NASA standard code with generators g(exp 1) = 1+D(exp 2)+D(exp 3)+D(exp 5)+D(exp 6) and g(exp 2) = 1+D+D(exp 2)+D(exp 3)+D(exp 6) and d(sub free) = 10. The channel interleaver is of the convolutional or periodic type. The binary output of the channel interleaver is transmitted across the channel using binary phase shift keying (BPSK) modulation. The transmitted symbols are corrupted by an RFI/burst channel consisting of a combination of additive white Gaussian noise (AWGN) and RFI pulses. At the receiver, a soft-decision Viterbi decoder with no quantization and variable truncation length is used to decode the deinterleaved sequence.

Perez, Lance C.↗

NASA NTRS2023

Characterization of Errors in Satellite-Based HCHO/NO 2 Tropospheric Column Ratios With Respect to Chemistry, Column-to-PBL Translation, Spatial Representation, and Retrieval Uncertainties

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LRO x ) to the chemical loss of NO x (LNO x ). Subsequently, we challenge the predictive power of HCHO/NO 2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LRO x /LNO x . FNRs show a strongly linear (R 2 =0.94) relationship with LRO x /LNO x , but only on the logarithmic scale. Following the baseline (i.e., ln(LRO x /LNO x ) = −1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NO x -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the RO x –HO x cycle. We calculate high ozone production rates (PO 3 ) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NO x -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2 ). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm −2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric.

Amir H. Souri↗

NASA NTRS1996

Iterative LQG Controller Design Through Closed-Loop Identification

This paper presents an iterative Linear Quadratic Gaussian (LQG) controller design approach for a linear stochastic system with an uncertain open-loop model and unknown noise statistics. This approach consists of closed-loop identification and controller redesign cycles. In each cycle, the closed-loop identification method is used to identify an open-loop model and a steady-state Kalman filter gain from closed-loop input/output test data obtained by using a feedback LQG controller designed from the previous cycle. Then the identified open-loop model is used to redesign the state feedback. The state feedback and the identified Kalman filter gain are used to form an updated LQC controller for the next cycle. This iterative process continues until the updated controller converges. The proposed controller design is demonstrated by numerical simulations and experiments on a highly unstable large-gap magnetic suspension system.

Hsiao, Min-Hung↗

NASA NTRS1992

The structure of intense vorticity in homogeneous isotropic turbulence

The structure of the intense vorticity regions is studied in numerically simulated homogeneous, isotropic, equilibrium turbulent flow fields at four different Reynolds numbers in the range Re(sub lambda) = 36-171. In accordance with previous investigators, this vorticity is found to be organized in coherent, cylindrical or ribbon-like, vortices ('worms'). A statistical study suggests that they are just especially intense features of the background, O(omega'), vorticity. Their radii scale with the Kolmogorov microscale and their lengths with the integral scale of the flow. An interesting observation is that the Reynolds number based on the circulation of the intense vortices, gamma/nu, increases monotonically with Re(sub lambda), raising the question of the stability of the structures in the limit of Re(sub lambda) approaching infinity. One and two-dimensional statistics of vorticity and strain are presented; they are non-gaussian, and the behavior of their tails depends strongly on the Reynolds number. There is no evidence of convergence to a limiting distribution in our range of Re(sub lambda), even though the energy spectra and the energy dissipation rate show good asymptotic properties in the higher Reynolds number cases. Evidence is presented to show that worms are natural features of the flow and that they do not depend on the particular forcing scheme.

Jimenez, J.↗

NASA NTRS1983

Terminal area automatic navigation, guidance and control research using the Microwave Landing System (MLS). Part 5: Design and development of a Digital Integrated Automatic Landing System (DIALS) for steep final approach using modern control techniques

The design and development of a 3-D Digital Integrated Automatic Landing System (DIALS) for the Terminal Configured Vehicle (TCV) Research Aircraft, a B-737-100 is described. The system was designed using sampled data Linear Quadratic Gaussian (LOG) methods, resulting in a direct digital design with a modern control structure which consists of a Kalman filter followed by a control gain matrix, all operating at 10 Hz. DIALS uses Microwave Landing System (MLS) position, body-mounted accelerometers, as well as on-board sensors usually available on commercial aircraft, but does not use inertial platforms. The phases of the final approach considered are the localizer and glideslope capture which may be performed simultaneously, localizer and steep glideslope track or hold, crab/decrab and flare to touchdown. DIALS captures, tracks and flares from steep glideslopes ranging from 2.5 deg to 5.5 deg, selected prior to glideslope capture. Digital Integrated Automatic Landing System is the first modern control design automatic landing system successfully flight tested. The results of an initial nonlinear simulation are presented here.

Halyo, N.↗

NASA NTRS2019

Characterizing the System Impulse Response Function from Photon-Counting LiDAR Data

NASA's Multiple Altimeter Beam Experimental LiDAR (MABEL) is an aircraft-based photon-counting laser altimeter designed as a simulator to test measurement techniques and algorithms for Advanced Topographic Laser Altimeter System (ATLAS), the sole instrument on NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. By measuring the time of flight, pointing angle, and absolute position for individual photons, ICESat-2 provides detailed elevation measurements of earth's surface. Calculating accurate and precise elevations requires an understanding of how photons interact with surfaces, and characterization of the photon distribution after returning from surfaces. Neither MABEL nor ATLAS records the transmitted laser pulse shape, relying instead on aggregating several pulses worth of photons, often using histograms, to characterize the pulse shape. In this paper, we assess the limitations of using histograms and propose a more robust method to describe MABEL's system impulse-response function using an exponentially modified Gaussian distribution. We also provide standard error estimates for the arithmetic mean and standard deviation calculations, and for exponentially modified Gaussian parameters using a Monte Carlo sensitivity analysis. We apply this method to photon returns from a sea ice lead and from a dry salt lake bed as case studies for estimating the standard error associated with sample size for the arithmetic mean and standard deviation, and for the exponentially modified Gaussian parameters. We use these standard errors to calculate the minimum number of photons required to find both Gaussian and exponentially modified Gaussian distribution parameters within 3 cm of their parent population values.

photoncounting↗

NASA NTRS2022

Searching for Quasi-periodic Oscillations in Astrophysical Transients Using Gaussian Processes

Analyses of quasi-periodic oscillations(QPOs)are important to understanding the dynamic behavior in manyastrophysical objects during transient events like gamma-ray bursts, solarflares, magnetarflares, and fast radiobursts. Astrophysicists often search for QPOs with frequency-domain methods such as(Lomb–Scargle)periodograms, which generally assume power-law models plus some excess around the QPO frequency. Time-series data can alternatively be investigated directly in the time domain using Gaussian process(GP)regression.While GP regression is computationally expensive in the general case, the properties of astrophysical data andmodels allow fast likelihood strategies. Heteroscedasticity and nonstationarity in data have been shown to causebias in periodogram-based analyses. GPs can take account of these properties. Using GPs, we model QPOs as astochastic process on top of a deterministicflare shape. Using Bayesian inference, we demonstrate how to infer GPhyperparameters and assign them physical meaning, such as the QPO frequency. We also perform model selectionbetween QPOs and alternative models such as red noise and show that this can be used to reliablyfind QPOs. Thismethod is easily applicable to a variety of different astrophysical data sets. We demonstrate the use of this methodon a range of short transients: a gamma-ray burst, a magnetarflare, a magnetar giantflare, and simulated solarflare data.

Moritz Hubner↗

NASA NTRSDate not supplied

Discriminative Methodology using the Unscented Transform in Special Euclidean Group SE(3) for Autonomous GN&C

Kalman filtering techniques usually compare a known dynamic model with some process noise to an updated, noisy measurement. Both sources of noise are generally assumed to be Gaussian and are filtered to obtain a more accurate estimate of the state of the system of interest. However, these methods assume that a relatively accurate dynamical model already exists. By including discriminative methodology to interpret differences in the predictive model and the measured states over time, an incorrect model can be corrected overtime, allowing a spacecraft to learn about its environment and adapt to changing conditions. In this paper, a discriminative unscented Kalman filter (DUKF) is introduced on the special Euclidean group SE(3) formulation framework. A spacecraft is initialized near a small body with no knowledge of its parameters, and using several consecutive conditional models the environment is studied and the filter is updated. The case study of a spacecraft in a slightly elliptical, inclined, relatively tight orbit around the irregular moon Phobos is simulated and discussed. The accuracy of this approach is quantifying the differences between the true state, the UKF with a poor model, and the DUKF.

GN&C↗

NASA NTRS1992

LES versus DNS: A comparative study

We have performed Direct Numerical Simulations (DNS) and Large Eddy Simulations (LES) of forced isotropic turbulence at moderate Reynolds numbers. The subgrid scale model used in the LES is based on an eddy viscosity which adjusts instantaneously the energy spectrum of the LES to that of the DNS. The statistics of the large scales of the DNS (filtered DNS field or fDNS) are compared to that of the LES. We present results for the transfer spectra, the skewness and flatness factors of the velocity components, the PDF's of the angle between the vorticity and the eigenvectors of the rate of strain, and that between the vorticity and the vorticity stretching tensor. The above LES statistics are found to be in good agreement with those measured in the fDNS field. We further observe that in all the numerical measurements, the trend was for the LES field to be more gaussian than the fDNS field. Future research on this point is planned.

Shtilman, L.↗

NASA NTRSDate not supplied

Clutter Assessment for an Autonomous Multi-Agent Search Mission

This paper presents a method for evaluating the amount of clutter in a region where autonomous vehicles in a multi-agent system must operate based on LIDAR point cloud measurements. The point cloud is used to generate an occupancy grid which is then projected onto a 2D plane of vehicle motion, constituting an image. A series of Gaussian radial basis functions (GRBFs) is created, each centered at an occupied pixel in a 2D image, and summed together to form the clutter field. The clutter field is a representation of the density and permeability of the space at each coordinate. The clutter field is then approximated such that iso-clutter contours are simple geometric objects so that intelligent machine assets can easily query the distance between them and any given point in an environment. In this way, agents are able to determine whether to enter into or steer away from areas of interest. Each vehicle has a clutter threshold representing the clutter value of the space in which it can safely maneuver. The iso-clutter contour corresponding to a vehicle’s clutter threshold is treated as the boundary of an obstacle to be avoided. A simulation is presented where a multi-agent system is tasked with persistent observation of a cluttered area. Each vehicle in the simulation has a different clutter threshold. The vehicles use a potential field-based guidance algorithm, and an allocation of vehicles to specific regions of the space emerges.

multi-agent↗

NASA NTRS2003

Self-Consistent Model of Magnetospheric Ring Current and Electromagnetic Ion Cyclotron Waves: The 2-7 May 1998 Storm

A complete description of a self-consistent model of magnetospheric ring current interacting with electromagnetic ion cyclotron waves is presented. The model is based on the system of two kinetic equations; one equation describes the ring current ion dynamics, and another equation describes the wave evolution. The effects on ring current ions interacting with electromagnetic ion cyclotron waves and back on waves are considered self-consistently by solving both equations on a global magnetospheric scale under nonsteady state conditions. The developed model is employed to simulate the entire 2-7 May 1998 storm period. First, the trapped number fluxes of the ring current protons are calculated and presented along with comparison with the data measured by the three- dimensional hot plasma instrument Polar/HYDRA. Incorporating in the model the wave-particle interaction leads to much better agreement between the experimental data and the model results. Second, examining of the wave (MLT, L shell) distributions produced by the model during the storm progress reveals an essential intensification of the wave emission about 2 days after the main phase of the storm. This result is well consistent with the earlier ground-based observations. Finally, the theoretical shapes and the occurrence rates of the wave power spectral densities are studied. It is found that about 2 days after the storm s main phase on 4 May, mainly non-Gaussian shapes of power spectral densities are produced.

Khazanov, G. V.↗

NASA NTRS1996

Optimum combining of residual carrier array signals in correlated noises

An array feed combining system for the recovery of signal-to-noise ratio (SNR) loss due to antenna reflector deformation has been implemented and is currently being evaluated on the Jet Propulsion Laboratory 34-m DSS-13 antenna. The current signal-combining system operates under the assumption that the white Gaussian noise processes in the received signals from different array elements are mutually uncorrelated. However, experimental data at DSS 13 indicate that these noise processes are indeed mutually correlated. The objective of this work is to develop a signal-combining system optimized to account for the mutual correlations between these noise processes. The set of optimum combining weight coefficients that maximizes the combined signal SNR in the correlated noises environment is determined. These optimum weights depend on unknown signal and noise covariance parameters. A maximum-likelihood approach is developed to estimate these unknown parameters to obtain estimates of the optimum weight coefficients based on residual carrier signal samples. The actual combined signal SNR using the estimated weight coefficients is derived and shown to converge to the maximum achievable SNR as the number of signal samples increases. These results are also verified by simulation. A numerical example shows a significant improvement in SNR performance can be obtained, especially when the amount of correlation increases.

Liang, R.↗

NASA NTRS1996

Optimum Combining of Residual Carrier Array Signals in Correlated Noises

Tan, H. H.↗

NASA NTRS2003

Translocation of a Polymer Chain across a Nanopore: A Brownian Dynamics Simulation Study

We carried out Brownian dynamics simulation studies of the translocation of single polymer chains across a nanosized pore under the driving of an applied field (chemical potential gradient). The translocation process can be either dominated by the entropic barrier resulted from restricted motion of flexible polymer chains or by applied forces (or chemical gradient across the wall), we focused on the latter case in our studies. Calculation of radius of gyrations at the two opposite sides of the wall shows that the polymer chains are not in equilibrium during the translocation process. Despite this fact, our results show that the one-dimensional diffusion and the nucleation model provide an excellent description of the dependence of average translocation time on the chemical potential gradients, the polymer chain length and the solvent viscosity. In good agreement with experimental results and theoretical predictions, the translocation time distribution of our simple model shows strong non-Gaussian characteristics. It is observed that even for this simple tubelike pore geometry, more than one peak of translocation time distribution can be generated for proper pore diameter and applied field strengths. Both repulsive Weeks-Chandler-Anderson and attractive Lennard-Jones polymer-nanopore interaction were studied, attraction facilitates the translocation process by shortening the total translocation time and dramatically improve the capturing of polymer chain. The width of the translocation time distribution was found to decrease with increasing temperature, increasing field strength, and decreasing pore diameter.

Tian, Pu↗

NASA NTRSDate not supplied

Aeroservoelastic Control Law Development for the Integrated Adaptive Wing Technology Maturation Wind-Tunnel Test

In this paper, a linear quadratic Gaussian (LQG) regulator was applied to a computational aeroservoelastic (ASE) model of the Integrated Adaptive Wing Technology Maturation (IAWTM) wind-tunnel model to demonstrate its effectiveness for active flutter suppression. The aerodynamics within this computational ASE model were solved using unsteady Reynolds-averaged Navier-Stokes (RANS) equations; the structural dynamics of the model were solved using modal analysis. This RANS-based ASE model was used as the plant for the LQG regulator. The Kalman filter and controller used within the LQG regulator were derived from a reduced-order model (ROM) of the RANS-based ASE model. This ROM-based ASE model was generated using system identification techniques. It was shown that the Kalman filter adequately predicted important states of the plant, and that LQG regulator successfully stabilized an aeroelastically unstable plant without exceeding reasonable control surface limitations. All of this was demonstrated using simulation data, and the methods presented here appear feasible for use in the upcoming IAWTM wind-tunnel tests.

Josiah M. Waite↗