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At least 109 records · Page 6

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NASA NTRSDate not supplied

Design of a Thrust Vector Servoelastic Filter for SLS Block 2 Booster Thrust Vector Control System

This paper presents a method to improve the thrust vector servoelastic (TVSE) response of a launch vehicle. TVSE is the coupling between the Thrust Vector Control (TVC) system nozzle dynamics and the vehicle flexible modes. A poorly phased TVC response, i.e. in phase with the structural velocity, can lead to instability of the flexible modes due to the energy injection from the thrust. For large boosters with heavy nozzles, TVSE is more likely to cause instability. This instability is part of the plant dynamics and may not be readily detected by the flight control system. In this paper, TVSE is treated as a disturbance rejection problem with the inertial force of the flexible motion viewed as an external disturbance to the TVC actuator control system. By effectively rejecting this disturbance, the engine can be decoupled from the flexible dynamics thus improving TVSE stability. The actuator disturbance transfer function is modified by inserting a filter into the servo-loop control system. The filter aims to reduce the magnitude and introduce phase lead of the disturbance transfer function over the TVSE sensitive frequency range while maintaining adequate stability margins of the actuator control system. A prefilter is also designed to improve command tracking performance. The filter and prefilter resulting from this method are usually of low order and can be included to an existing actuator controller if the controller is programmable. This method was demonstrated for a hydraulic Simplex actuator model. Its applications to the Space Launch System (SLS) Block 1 and Block 2 TVC actuator are also described. The Block 2 actuator controller was modified based on the results of this method. The tradeoff between TVSE stability and the servo-loop stability can be balanced by adjusting the amount of phase lead introduced by the TVSE filter. This method provides a useful way to solve the TVSE instability issue without costly and time-consuming hardware solutions. This method is based on the basic control principles of loop shaping and disturbance rejection and has been proven to be effective under proper circumstances.

Thrust vector control↗

NASA NTRS1976

Development of an optimal automatic control law and filter algorithm for steep glideslope capture and glideslope tracking

A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.

Halyo, N.↗

NASA NTRS1987

SIR-B ocean-wave enhancement with fast Fourier transform techniques

Shuttle Imaging Radar (SIR-B) imagery is Fourier filtered to remove the estimated system-transfer function, reduce speckle noise, and produce ocean scenes with a gray scale that is proportional to wave height. The SIR-B system response to speckled scenes of uniform surfaces yields an estimate of the stationary wavenumber response of the imaging radar, modeled by the 15 even terms of an eighth-order two-dimensional polynomial. Speckle can also be used to estimate the dynamic wavenumber response of the system due to surface motion during the aperture synthesis period, modeled with a single adaptive parameter describing an exponential correlation along track. A Fourier filter can then be devised to correct for the wavenumber response of the remote sensor and scene correlation, with subsequent subtraction of an estimate of the speckle noise component. A linearized velocity bunching model, combined with a surface tilt and hydrodynamic model, is incorporated in the Fourier filter to derive estimates of wave height from the radar intensities corresponding to individual picture elements.

Tilley, David G.↗

NASA NTRS1989

Application of a single area array detector for acquistion, tracking and point-ahead in space optical communications

Functions of acquisition, tracking, and point-ahead in space optical communications are being combined into a single system utilizing an area array detector. An analysis is presented of the feasibility concept. The key parameters are: optical power less than 1 pW at 0.86 micrometer, acquisition in less than 30 seconds in an acquisition field of view (FOV) of 1 mrad, tracking with 0.5 microrad rms noise at 1000 Hz update rate, and point ahead transfer function precision of 0.25 microrad over a region of 150 microrad. Currently available array detectors were examined. The most demanding specifications are low output noise, a high detection efficiency, a large number of pixels, and frame rates over 1kHz. A proof of concept (POC) demonstration system is currently being built utilizing the Kodak HS-40 detector (a 128 x 128 photodiode array with a 64 channel CCD readout architecture which can be operated at frame rates as high as 40,000/sec). The POC system implements a windowing scheme and special purpose digital signal processing electronic for matched filter acquisition and tracking algorithms.

Clark, D. L.↗

NASA NTRS1989

Application of a single area array detector for acquisition, tracking and point-ahead in space optical communications

Clark, D. L.↗

NASA NTRS1972

Nonlinear and adaptive estimation techniques in reentry

The development and testing of nonlinear and adaptive estimators for reentry (e.g. space shuttle) navigation and model parameter estimation or identification are reported. Of particular interest is the identifcation of vehicle lift and drag characteristics in real time. Several nonlinear filters were developed and simulated. Adaptive filters for the real time identification of vehicle lift and drag characteristics, and unmodelable acceleration, were also developed and tested by simulation. The simulations feature an uncertain system environment with rather arbitrary model errors, thus providing a definitive test of estimator performance. It was found that nonlinear effects are indeed significant in reentry trajectory estimation and a nonlinear filter is demonstrated which successfully tracks through nonlinearities without degrading the information content of the data. Under the same conditions the usual extended Kalman filter diverges and is useless. The J-adaptive filter is shown to successfully track errors in the modeled vehicle lift and drag characteristics. The same filter concept is also shown to track successfully through rather arbitrary model errors, including lift and drag errors, vehicle mass errors, atmospheric density errors, and wind gust errors.

Jazwinski, A. H.↗

NASA NTRS2016

Orion Exploration Flight Test 1 (EFT-1) Best Estimated Trajectory Development

The Orion Exploration Flight Test 1 (EFT-1) mission successfully flew on Dec 5, 2014 atop a Delta IV Heavy launch vehicle. The goal of Orions maiden flight was to stress the system by placing an uncrewed vehicle on a high-energy trajectory replicating conditions similar to those that would be experienced when returning from an asteroid or a lunar mission. The Orion navigation team combined all trajectory data from the mission into a Best Estimated Trajectory (BET) product. There were significant challenges in data reconstruction and many lessons were learned for future missions. The team used an estimation filter incorporating radar tracking, onboard sensors (Global Positioning System and Inertial Measurement Unit), and day-of-flight weather balloons to evaluate the true trajectory flown by Orion. Data was published for the entire Orion EFT-1 flight, plus objects jettisoned during entry such as the Forward Bay Cover. The BET customers include approximately 20 disciplines within Orion who will use the information for evaluating vehicle performance and influencing future design decisions.

Holt, Greg N.↗

NASA NTRS2011

Kalman Orbit Optimized Loop Tracking

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

Young, Lawrence E.↗

NASA NTRS1974

Real-time shipboard orbit determination using Kalman filtering techniques

The real-time tracking and orbit determination program used on board the NASA tracking ship, the USNS Vanguard, is described in this paper. The computer program uses a variety of filtering algorithms, including an extended Kalman filter, to derive real-time orbit determinations (position-velocity state vectors) from shipboard tracking and navigation data. Results from Apollo missions are given to show that orbital parameters can be estimated quickly and accurately using these methods.

Brammer, R. F.↗

NASA NTRS1972

Nonlinear and adaptive estimation in reentry.

The problem of real-time estimation of a lifting reentry vehicle trajectory of the shuttle orbiter type is considered. Simulations feature large position and velocity uncertainties at radar acquisition and realistic model errors in lift, drag and other model parameters. Radar tracking and accelerometer data are simulated. Significant nonlinearities are found to exist on spacecraft acquisition. An iterated nonlinear filter is shown to perform optimally during the radar acquisition phase. An adaptive filter is shown to track time-varying model errors, such as errors in the lift and drag coefficients, down to the noise level. Such real-time model tracking (identification) is frequently required for guidance and control implementation.

Jazwinski, A. H.↗

NASA NTRS1984

A nonlinear filter for compensating for time delays in manual control systems

A nonlinear filter configured to provide phase lead without accompanying gain distortion is analyzed and evaluated. The nonlinear filter is superior to a linear lead/lag compensator in its ability to maintain system stability as open loop crossover frequency is increased. Test subjects subjectively rated the filter as slightly better than a lead/lag compensator in its ability to compensate for delays in a compensatory tracking task. However, the filter does introduce unwanted harmonics. This is particularly noticeable for low frequency pilot inputs. A revised compensation method is proposed which allows such low frequency inputs to bypass the nonlinear filter. A brief analytical and experimental evaluation of the revised filter indicates that further evaluation in more realistic tasks is justified.

Hess, R. A.↗

NASA NTRS1983

Hardware verification of distributed/adaptive control

Adaptive control techniques are studied for their future application to the control of large space structures, where uncertain or changing parameters may destabilize standard control system designs. The approach used is to examine an extended Kalman filter estimator, in which the state vector is augmented with the unknown parameters. The associated Riccatti equation is linearized about the case of exact knowledge of the parameters. By assuming that parameter variations occur slowly, the filter complexity is reduced further yet. Simulations on a two degree-of-freedom oscillator demonstrate the parameter-tracking capability of the filter, and an implementation on the JPL Flexible Beam Facility using an incorrect model shows the adaptive filter/optimal control to be stable where a standard Kalman filter/optimal control design is unstable.

Eldred, D. B.↗

NASA NTRS1995

Filtering Image Records Using Wavelets and the Zakai Equation

Consider the problem of detecting and localizing a faint object moving In an "essentially stationary" background, using a sequence of two-dimensional low-SNR images of the scene. A natural approach consists of "digitizing" each snapshot into a discrete set of observations, sufficiently (perhaps not exactly) matched to the object In question, then tracking the object using an appropriate stochastic filter. The tracking would be expected to make up for the low signal-to-noise ratio, this allowing one to "coherently" process successive images in order to beat down the noise and localize the object. Thus, "tracking" here does not refer to the usual notion of detecting then tracking: rather, we track in order to detect The problem then becomes one of choosing the appropriate image representation as well as the optimal (and necessarily nonlinear filter. We propose exact and approximate solutions using wavelets and the Zakai equation. The smoothness of the wavelets used is required in the derivation of the evolution equation for the conditional density giving the filter, and their orthogonality makes it possible to carry out actual computations of the Ito- and change-of-gauge-terms in the algorithm effectively.

Haddad, Ziad S.↗

NASA NTRSDate not supplied

Distributed Target Tracking With Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using dynamic information fusion from multi-modal sensors with geodiversity. First, the algorithm execution location is determined using an optimal data migration strategy, next the sensors information is dynamically fused at each estimation instance using validity flag for each sensor reading, finally the target estimation is updated based on the fused innovation vector. The approach is applied to synthetic data generated from the radar and camera models located on the ground for the simulated target flight in Reflection simulation environment.

Distributed sensing↗

NASA NTRS1972

Solar particle tracks in glass from Surveyor 3

Samples of glass from the Surveyor 3 TV camera filter were examined for particle tracks by optical and scanning electron microscopy. The corrected density value is 1.7 million + or - 0.1 million tracks/sq cm, and the track density vs depth curve is determined. Comparisons with other estimated and calculated data are discussed, and lack of agreement between data sets is considered. It is felt that considerable erosion occurs, and that erosion also occurs by a flaking of small thicknesses of material, possibly caused by solar wind irradiation.

Crozaz, G.↗

NASA NTRS1987

Optimum filters and smoothers design for carrier phase and frequency tracking

The report presents the application of fixed lag smoothing algorithms to the problem of estimation of the phase and frequency of a sinusoidal carrier received in the presence of process noise and additive observation noise. A suboptimal structure consists of a phase-locked loop (PLL) followed by post-loop correction to the phase and frequency estimates. When the PLL is operating under high signal-to-noise ratio, the phase detector is approximately linear, and the smoother equations then correspond to the optimal linear equations for an equivalent linear signal model. The performance of such a smoother can be predicted by linear filtering theory. However, if the PLL is operating near the threshold region of the signal-to-noise ratio, the phase detector cannot be assumed to be linear. Then the actual performance of the smoother can significantly differ from that predicted by linear theory. In this report we present both the theoretical and simulated performance of such smoothers derived on the basis of various models for the phase and frequency processes.

Kumar, Rajendra↗

NASA NTRS1994

Groundspeed filtering for CTAS

Ground speed is one of the radar observables which is obtained along with position and heading from NASA Ames Center radar. Within the Center TRACON Automation System (CTAS), groundspeed is converted into airspeed using the wind speeds which CTAS obtains from the NOAA weather grid. This airspeed is then used in the trajectory synthesis logic which computes the trajectory for each individual aircraft. The time history of the typical radar groundspeed data is generally quite noisy, with high frequency variations on the order of five knots, and occasional 'outliers' which can be significantly different from the probable true speed. To try to smooth out these speeds and make the ETA estimate less erratic, filtering of the ground speed is done within CTAS. In its base form, the CTAS filter is a 'moving average' filter which averages the last ten radar values. In addition, there is separate logic to detect and correct for 'outliers', and acceleration logic which limits the groundspeed change in adjacent time samples. As will be shown, these additional modifications do cause significant changes in the actual groundspeed filter output. The conclusion is that the current ground speed filter logic is unable to track accurately the speed variations observed on many aircraft. The Kalman filter logic however, appears to be an improvement to the current algorithm used to smooth ground speed variations, while being simpler and more efficient to implement. Additional logic which can test for true 'outliers' can easily be added by looking at the difference in the a priori and post priori Kalman estimates, and not updating if the difference in these quantities is too large.

Slater, Gary L.↗

NASA NTRS1978

Tracking performance of unbalanced QPSK demodulators. II - Biphase Costas loop with active arm filters

In a Costas loop study for biphase modulation conducted by Simon and Lindsey (1977), it was demonstrated that considerable improvement in tracking performance could be obtained by employing active arm filters of the integrate-and-dump type as opposed to passive arm filters. An investigation is conducted concerning the possibility to obtain a similar performance improvement for an unbalanced quadriphase-shift-keying (QPSK) modulation. It is found that the biphase Costas loop can be used as an efficient demodulator of QPSK in cases in which the ratio of data rates is of the same order of magnitude as the inverse of the power ratio. These cases involve approximately equal signal energies in the two channels.

Simon, M. K.↗