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At least 253 records · Page 14

Modeling Kepler Transit Light Curves as False Positives: Rejection of Blend Scenarios for Kepler-9, and Validation of Kepler-9 d, a Super-Earth-Size Planet in a Multiple System

Light curves from the Kepler Mission contain valuable information on the nature of the phenomena producing the transit-like signals. To assist in exploring the possibility that they are due to an astrophysical false positive we describe a procedure (BLENDER) to model the photometry in terms of a blend rather than a planet orbiting a star. A blend may consist of a background or foreground eclipsing binary (or star-planet pair) whose eclipses are attenuated by the light of the candidate and possibly other stars within the photometric aperture. We apply BLENDER to the case of Kepler-9 (KIC 3323887), a target harboring two previously confirmed Saturn-size planets (Kepler-9 b and Kepler-9 c) showing transit timing variations, and an additional shallower signal with a 1.59 day period suggesting the presence of a super-Earth-size planet. Using BLENDER together with constraints from other follow-up observations we are able to rule out all blends for the two deeper signals and provide independent validation of their planetary nature. For the shallower signal, we rule out a large fraction of the false positives that might mimic the transits. The false alarm rate for remaining blends depends in part (and inversely) on the unknown frequency of small-size planets. Based on several realistic estimates of this frequency, we conclude with very high confidence that this small signal is due to a super-Earth-size planet (Kepler-9 d) in a multiple system, rather than a false positive. The radius is determined to be 1.64(exp)(sub-14),R, and current spectroscopic observations are as yet insufficient to establish its mass.

PLANETARY SYSTEMS↗

Assessment and Control of Spacecraft Charging Risks on the International Space Station

The International Space Station (ISS) operates in the F2 region of Earth's ionosphere, orbiting at altitudes ranging from 350 to 450 km at an inclination of 51.6 degrees. The relatively dense, cool F2 ionospheric plasma suppresses surface charging processes much of the time, and the flux of relativistic electrons is low enough to preclude deep dielectric charging processes. The most important spacecraft charging processes in the ISS orbital environment are: 1) ISS electrical power system interactions with the F2 plasma, 2) magnetic induction processes resulting from flight through the geomagnetic field and, 3) charging processes that result from interaction with auroral electrons at high latitude. Recently, the continuing review and evaluation of putative ISS charging hazards required by the ISS Program Office revealed that ISS charging could produce an electrical shock hazard to the ISS crew during extravehicular activity (EVA). ISS charging risks are being evaluated in an ongoing measurement and analysis campaign. The results of ISS charging measurements are combined with a recently developed model of ISS charging (the Plasma Interaction Model) and an exhaustive analysis of historical ionospheric variability data (ISS Ionospheric Specification) to evaluate ISS charging risks using Probabilistic Risk Assessment (PRA) methods. The PRA combines estimates of the frequency of occurrence and severity of the charging hazards with estimates of the reliability of various hazard controls systems, as required by NASA s safety and risk management programs, to enable design and selection of a hazard control approach that minimizes overall programmatic and personnel risk. The PRA provides a quantitative methodology for incorporating the results of the ISS charging measurement and analysis campaigns into the necessary hazard reports, EVA procedures, and ISS flight rules required for operating ISS in a safe and productive manner.

Koontz, Steve↗

Computationally Efficient Frequency Domain Method for Dynamic Control Derivative Estimation with Application to Transonic Truss-Braced Wing

This paper presents a computationally efficient method for dynamic control derivative estimation technique via control surface oscillation numerical experiments. Unsteady RANS CFD simulations in FUN3D are performed to simulate the control surface oscillations with a prescribed truncated square wave containing sufficient frequencies of interest. The truncated square wave oscillation offers the computational efficiency which reduces the computational cost by almost an order of magnitude compared to a sine wave oscillation. The nonlinear effect of large control surface oscillation amplitudes creates a spillover effect whereby the frequency response at the same input frequencies contains not only the linear aerodynamic response but also nonlinear aerodynamic response. A correction procedure is developed to remove the spillover effect from the linear aerodynamic response. A frequency-domain regression is performed to estimate the dynamic control derivatives after the correction. The results generally agree with the previous results obtained from the sine wave oscillation.

Stability and Control↗

The use of the experimentally deduced Brunt-Vaisala frequency and turbulent velocity fluctuations to estimate the eddy diffusion coefficient

The determination of the turbulent energy dissipation rate or the eddy diffusion coefficient from radar observations can be done through the turbulence refractive index structure constant, deduced from calibrated echo power measurements, or through the turbulent velocity fluctuations, deduced from the echo spectrum width. Besides the radar parameters, power and spectrum width, the first approach needs knowledge of profiles of temperature and electron density in the mesosphere and the fraction of the radar volume filled with turbulence. The latter approach needs knowledge of the temperature profile, namely, the Brunt-Vaisala frequency. The use of this latter approach is demonstrated.

Rottger, J.↗

Maximum likelihood method for estimating airplane stability and control parameters from flight data in frequency domain

A frequency domain maximum likelihood method is developed for the estimation of airplane stability and control parameters from measured data. The model of an airplane is represented by a discrete-type steady state Kalman filter with time variables replaced by their Fourier series expansions. The likelihood function of innovations is formulated, and by its maximization with respect to unknown parameters the estimation algorithm is obtained. This algorithm is then simplified to the output error estimation method with the data in the form of transformed time histories, frequency response curves, or spectral and cross-spectral densities. The development is followed by a discussion on the equivalence of the cost function in the time and frequency domains, and on advantages and disadvantages of the frequency domain approach. The algorithm developed is applied in four examples to the estimation of longitudinal parameters of a general aviation airplane using computer generated and measured data in turbulent and still air. The cost functions in the time and frequency domains are shown to be equivalent; therefore, both approaches are complementary and not contradictory. Despite some computational advantages of parameter estimation in the frequency domain, this approach is limited to linear equations of motion with constant coefficients.

Klein, V.↗

Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar

Ground clutter interference is a major problem for airborne pulse Doppler radar operating at low altitudes in a look-down mode. With Doppler zero set at the aircraft ground speed, ground clutter rejection filtering is typically accomplished using a high-pass filter with real valued coefficients and a stopband notch centered at zero Doppler. Clutter spectra from the NASA Wind Shear Flight Experiments of l991-1992 show that the dominant clutter mode can be located away from zero Doppler, particularly at short ranges dominated by sidelobe returns. Use of digital notch filters with complex valued coefficients so that the stopband notch can be located at any Doppler frequency is investigated. Several clutter mode tracking algorithms are considered to estimate the Doppler frequency location of the dominant clutter mode. From the examination of night data, when a dominant clutter mode away from zero Doppler is present, complex filtering is able to significantly increase clutter rejection over use of a notch filter centered at zero Doppler.

Jamora, Dennis A.↗

Non-intrusive parameter identification procedure user's guide

Written in standard FORTRAN, NAS is capable of identifying linear as well as nonlinear relations between input and output parameters; the only restriction is that the input/output relation be linear with respect to the unknown coefficients of the estimation equations. The output of the identification algorithm can be specified to be in either the time domain (i.e., the estimation equation coefficients) or in the frequency domain (i.e., a frequency response of the estimation equation). The frame length ("window") over which the identification procedure is to take place can be specified to be any portion of the input time history, thereby allowing the freedom to start and stop the identification procedure within a time history. There also is an option which allows a sliding window, which gives a moving average over the time history. The NAS software also includes the ability to identify several assumed solutions simultaneously for the same or different input data.

Hanson, G. D.↗

Review of specific antenna configurations: An estimate of cost and performance versus frequency for a simple (10 Lambda)-2 clear-air radar antenna array

The building of operational clear air radar wind profilers is discussed. The choice of operating frequency and antenna configuration for these profilers is examined. The cost and performance of a (10 lambda) 2 antenna array versus operating frequency over the range 30 to 400 MHz is compared. To simplify the comparison the array beam will be fixed and the array will be uniformly fed. Yagi and coaxial collinear (COCO) cable antennas are compared, although other configurations may be competitive. It is assumed that the array is driven by a typical 50 kW peak power, 1 kW average, power transmitter located at the array edge when calculating feedline power handling requirements and when system performance is compared. For this comparison an array aperture of (10 lambda) 2 was chosen since a one way beam width of 5 deg or less is desirable to limit beam spreading effects.

Ecklund, W. L.↗

Spontaneous fluctuations in cerebral blood flow: insights from extended-duration recordings in humans

To determine the dependence of cerebral blood flow (CBF) on arterial pressure over prolonged time periods, we measured beat-to-beat changes in mean CBF velocity in the middle cerebral artery (transcranial Doppler) and mean arterial pressure (Finapres) continuously for 2 h in six healthy subjects (5 men and 1 woman, 18-40 yr old) during supine rest. Fluctuations in velocity and pressure were quantified by the range [(peak - trough)/mean] and coefficients of variation (SD/mean) in the time domain and by spectral analysis in the frequency domain. Mean velocity and pressure over the 2-h recordings were 60 +/- 7 cm/s and 83 +/- 8 mmHg, associated with ranges of 77 +/- 8 and 89 +/- 10% and coefficients of variation of 9.3 +/- 2.2 and 7.9 +/- 2.3%, respectively. Spectral power of the velocity and pressure was predominantly distributed in the frequency range of 0.00014-0.1 Hz and increased inversely with frequency, indicating characteristics of an inverse power law (1/f(alpha)). However, linear regression on a log-log scale revealed that the slope of spectral power of pressure and velocity was steeper in the high-frequency (0.02-0.5 Hz) than in the low-frequency range (0.002-0.02 Hz), suggesting different regulatory mechanisms in these two frequency ranges. Furthermore, the spectral slope of pressure was significantly steeper than that of velocity in the low-frequency range, consistent with the low transfer function gain and low coherence estimated at these frequencies. We conclude that 1) long-term fluctuations in CBF velocity are prominent and similar to those observed in arterial pressure, 2) spectral power of CBF velocity reveals characteristics of 1/f(alpha), and 3) cerebral attenuation of oscillations in CBF velocity in response to changes in pressure may be more effective at low than that at high frequencies, emphasizing the frequency dependence of cerebral autoregulation.

NASA Discipline Cardiopulmonary↗

Statistical plant set estimation using Schroeder-phased multisinusoidal input design

A frequency domain method is developed for plant set estimation. The estimation of a plant 'set' rather than a point estimate is required to support many methods of modern robust control design. The approach here is based on using a Schroeder-phased multisinusoid input design which has the special property of placing input energy only at the discrete frequency points used in the computation. A detailed analysis of the statistical properties of the frequency domain estimator is given, leading to exact expressions for the probability distribution of the estimation error, and many important properties. It is shown that, for any nominal parametric plant estimate, one can use these results to construct an overbound on the additive uncertainty to any prescribed statistical confidence. The 'soft' bound thus obtained can be used to replace 'hard' bounds presently used in many robust control analysis and synthesis methods.

Bayard, D. S.↗

Center of Mass Estimation for a Spinning Spacecraft Using Doppler Shift of the GPS Carrier Frequency

A sequential filter is presented for estimating the center of mass (CM) of a spinning spacecraft using Doppler shift data from a set of onboard Global Positioning System (GPS) receivers. The advantage of the proposed method is that it is passive and can be run continuously in the background without using commanded thruster firings to excite spacecraft dynamical motion for observability. The NASA Magnetospheric Multiscale (MMS) mission is used as a test case for the CM estimator. The four MMS spacecraft carry star cameras for accurate attitude and spin rate estimation. The angle between the spacecraft nominal spin axis (for MMS this is the geometric body Z-axis) and the major principal axis of inertia is called the coning angle. The transverse components of the estimated rate provide a direct measure of the coning angle. The coning angle has been seen to shift slightly after every orbit and attitude maneuver. This change is attributed to a small asymmetry in the fuel distribution that changes with each burn. This paper shows a correlation between the apparent mass asymmetry deduced from the variations in the coning angle and the CM estimates made using the GPS Doppler data. The consistency between the changes in the coning angle and the CM provides validation of the proposed GPS Doppler method for estimation of the CM on spinning spacecraft.

Spacecraft↗

Center of Mass Estimation for a Spinning Spacecraft Using Doppler Shift of the GPS Carrier Frequency

A sequential filter is presented for estimating the center of mass (CM) of a spinning spacecraft using Doppler shift data from a set of onboard Global Positioning System (GPS) receivers. The advantage of the proposed method is that it is passive and can be run continuously in the background without using commanded thruster firings to excite spacecraft dynamical motion for observability. The NASA Magnetospheric Multiscale (MMS) mission is used as a test case for the CM estimator. The four MMS spacecraft carry star cameras for accurate attitude and spin rate estimation. The angle between the spacecraft nominal spin axis (for MMS this is the geometric body Z-axis) and the major principal axis of inertia is called the coning angle. The transverse components of the estimated rate provide a direct measure of the coning angle. The coning angle has been seen to shift slightly after every orbit and attitude maneuver. This change is attributed to a small asymmetry in the fuel distribution that changes with each burn. This paper shows a correlation between the apparent mass asymmetry deduced from the variations in the coning angle and the CM estimates made using the GPS Doppler data. The consistency between the changes in the coning angle and the CM provides validation of the proposed GPS Doppler method for estimation of the CM on spinning spacecraft.

Estimation↗

Natural frequency of uniform and optimized tetrahedral truss platforms

Qualitative and quantitative estimates for the fundamental frequency of uniform and optimized tetrahedral truss platforms are determined. A semiempirical equation is developed for the frequency of free-free uniform trusses as a function of member material properties, truss dimensions, and parasitic (nonstructural) mass fraction Mp/Mt. Optimized trusses with frequencies approximately two times those of uniform trusses are determined by varying the cross-sectional areas of member groups. Trusses with 3 to 8 rings, no parasitic mass, and member areas up to 25 times the minimum area are optimized. Frequencies computed for ranges of both Mp/Mt and the ratio of maximum area to minimum area are normalized to the frequency of a uniform truss with no parasitic mass. The normalized frequency increases with the number of rings, and both frequency and the ratio of maximum area to minimum area decrease with increasing Mp/Mt. Frequency improvements that are achievable with a limited number of member areas are estimated for a 3-ring truss by using Taguchi methods. Joint stiffness knockdown effects are also considered. Comparison of optimized and baseline uniform truss frequencies indicates that tailoring can significantly increase structural frequency; maximum gains occur for trusses with low values of Mp/Mt. This study examines frequency trends for ranges of structural parameters and may be used as a preliminary design guide.

Wu, K. Chauncey↗

Mars Global Surveyor Ka-Band Frequency Data Analysis

The Mars Global Surveyor (MGS) spacecraft, launched on November 7, 1996, carries an experimental space-to-ground telecommunications link at Ka-band (32 GHz) along with the primary X-band (8.4 GHz) downlink. The signals are simultaneously transmitted from a 1.5-in diameter parabolic high gain antenna (HGA) on MGS and received by a beam-waveguide (BWG) R&D 34-meter antenna located in NASA's Goldstone Deep Space Network (DSN) complex near Barstow, California. The projected 5-dB link advantage of Ka-band relative to X-band was confirmed in previous reports using measurements of MGS signal strength data acquired during the first two years of the link experiment from December 1996 to December 1998. Analysis of X-band and Ka-band frequency data and difference frequency (f(sub x)-f(sub ka)/3.8) data will be presented here. On board the spacecraft, a low-power sample of the X-band downlink from the transponder is upconverted to 32 GHz, the Ka-band frequency, amplified to I-W using a Solid State Power Amplifier, and radiated from the dual X/Ka HGA. The X-band signal is amplified by one of two 25 W TWTAs. An upconverter first downconverts the 8.42 GHz X-band signal to 8 GHz and then multiplies using a X4 multiplier producing the 32 GHz Ka-band frequency. The frequency source selection is performed by an RF switch which can be commanded to select a VCO (Voltage Controlled Oscillator) or USO (Ultra-Stable Oscillator) reference. The Ka-band frequency can be either coherent with the X-band downlink reference or a hybrid combination of the USO and VCO derived frequencies. The data in this study were chosen such that the Ka-band signal is purely coherent with the X-band signal, that is the downconverter is driven by the same frequency source as the X-band downlink). The ground station used to acquire the data is DSS-13, a 34-meter BWG antenna which incorporates a series of mirrors inside beam waveguide tubes which guide the energy to a subterranean pedestal room, providing a stable environment for the feed and electronics equipment. A dichroic plate is used to reflect the X-band energy and pass the Ka-band energy to another mirror. The RF energy for each band is then focused onto a feed horn and low-noise amplifier package. After amplification and RF/IF downconversion, the IF signals are sent to the Experimental Tone Tracker (ETT), a digital phase-lock-loop receiver, which simultaneously tracks both X-band and Ka-band carrier signals. Once a signal is detected, the ETT outputs estimates of the SNR in a I -Hz bandwidth (Pc/No), baseband phase and frequency of the signals every I -sec. Between December 1996 and December 1998, the Ka-band and X-band signals from MGS were tracked on a regular basis using the ETT. The Ka-band downlink frequencies described here were referenced to the spacecraft's on-board USO which was also the X-band frequency reference (f(sub ka)= 3.8 f(sub x)). The ETT estimates of baseband phase at I -second sampled time tags were converted to sky frequency estimates. Frequency residuals were then generated for each band by removing a model frequency from each observable frequency at each time tag. The model included Doppler and other effects derived from spacecraft trajectory files obtained from the MGS Navigation Team. A simple troposphere correction was applied to the data. In addition to residuals, the USO frequencies emitted by the spacecraft were estimated. For several passes, the USO frequencies were determined from X-band data and from Ka-band data (referred to X-band by dividing by 3.8) and were found to be in good agreement. In addition, X-band USO frequency estimates from MGS Radio Science data acquired from operational DSN stations were available for comparison and were found to agree within the I Hz level. The remaining sub-Hertz differences were attributed to the different models and software algorithms used by MGS Radio Science and KaBLE-11. A summary of the results of a linear fit of the USO frequency versus time (day of year) is presented in Table I for an initial segment of passes.

Morabito, D.↗

Adaptive Filtering for Large Space Structures: A Closed-Form Solution

In a previous paper Schaechter proposes using an extended Kalman filter to estimate adaptively the (slowly varying) frequencies and damping ratios of a large space structure. The time varying gains for estimating the frequencies and damping ratios can be determined in closed form so it is not necessary to integrate the matrix Riccati equations. After certain approximations, the time varying adaptive gain can be written as the product of a constant matrix times a matrix derived from the components of the estimated state vector. This is an important savings of computer resources and allows the adaptive filter to be implemented with approximately the same effort as the nonadaptive filter. The success of this new approach for adaptive filtering was demonstrated using synthetic data from a two mode system.

Rauch, H. E.↗

Short time-scale variability of chromospheric Ca II in late-type stars

The short time-scale variability of singly ionized calcium chromospheric emission has been investigated in a few late-type stars. Emission-line variations with time scales of a few minutes to hours are seen in Alpha Tau (K5 III), Lambda And (G8 III-IV), and Epsilon Eri (K2 V). The existence of substantial chromospheric flux changes (10 to the 30th to 10 to the 32nd ergs) over short periods of time suggests that the calcium emission arises from a few small, coherent regions. Frequencies present in the data are discussed in the context of acoustic wave predictions and estimated acoustic cutoff frequencies for giants and dwarfs.

Baliunas, S. L.↗

Estimation of Time-Varying Pilot Model Parameters

Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.

Zaal, Peter M. T.↗

Differential sampling for fast frequency acquisition via adaptive extended least squares algorithm

This paper presents a differential signal model along with appropriate sampling techinques for least squares estimation of the frequency and frequency derivatives and possibly the phase and amplitude of a sinusoid received in the presence of noise. The proposed algorithm is recursive in mesurements and thus the computational requirement increases only linearly with the number of measurements. The dimension of the state vector in the proposed algorithm does not depend upon the number of measurements and is quite small, typically around four. This is an advantage when compared to previous algorithms wherein the dimension of the state vector increases monotonically with the product of the frequency uncertainty and the observation period. Such a computational simplification may possibly result in some loss of optimality. However, by applying the sampling techniques of the paper such a possible loss in optimality can made small.

Kumar, Rajendra↗