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Several techniques exist for implementing integrated MOS filters. These techniques fit into the general categories of sampled and tuned continuous-time filters. Advantages and limitations of each approach are discussed. This paper focuses primarily on the high frequency capabilities of MOS integrated filters.
Converter uses solid-state ac-to-dc rectification circuitry, filter circuitry, a tuned transformer, ac chopper circuitry, and an automatic current-control network. It has a dc power source which operates from 5 to 100 percent load at a 72 to 94 input to output efficiency.
The design and fabrication are presented of a 65 cm photoheliograph functional verification unit (FVU) installed in a major solar observatory. The telescope is used in a daily program of solar observation while serving as a test bed for the development of instrumentation to be included in early space shuttle launched solar telescopes. The 65 cm FVU was designed to be mechanically compatible with the ATM spar/canister and would be adaptable to a second ATM flight utilizing the existing spar/canister configuration. An image motion compensation breadboard and a space-hardened, remotely tuned H alpha filter, as well as solar telescopes of different optical configurations or increased aperture are discussed.
A finite-difference essentially nonoscillatory (ENO) method has been applied to several of the problems prescribed for the workshop sponsored jointly by the Institute for Computer Applications in Science and Engineering and by NASA Langley Research Center entitled 'Benchmark Problems in Computational Aeroacoustics'. The workshop focused on computational challenges specific to aeroacoustics. Among these are long-distance propagation of a short-wavelength disturbance, propagation of small-amplitude disturbances, and nonreflective boundary conditions. The shock capturing-capability inherent to the ENO method effectively eliminates oscillations near shock waves without the need to add and tune dissipation or filter terms. The method-of-lines approach allows the temporal and spatial operators to be chosen separately in accordance with the demands of a particular problem. The ENO method was robust and accurate for all problems in which the propagating wave was resolved with 8 or more points per wavelength. The finite-wave-model boundary condition, a local nonlinear acoustic boundary condition, performed well for the one-dimensional problems. The buffer-domain approach performed well for the two-dimensional test problem. The amplitude of nonphysical reflections were less than 1 percent of the exiting wave's amplitude.
A scheme for stabilizing the frequency of a microwave signal is proposed that exploits the operational characteristics of a coupled optoelectronic oscillator (COEO) and related optoelectronic equipment. An essential element in the scheme is a fiber mode-locked laser (MLL), the optical frequency of which is locked to an atomic transition. In this scheme, the optical frequency stability of the mode-locked laser is transferred to that of the microwave in the same device. Relative to prior schemes for using wideband optical frequency comb to stabilize microwave signals, this scheme is simpler and lends itself more readily to implementation in relatively compact, rugged equipment. The anticipated development of small, low-power, lightweight, highly stable microwave oscillators based on this scheme would afford great benefits in communication, navigation, metrology, and fundamental sciences. COEOs of various designs, at various stages of development, in some cases called by different names, have been described in a number of prior NASA Tech Briefs articles. A COEO is an optoelectronic apparatus that generates both short (picosecond) optical pulses and a steady microwave signal having an ultrahigh degree of spectral purity. The term "coupled optoelectronic" in the full name of such an apparatus signifies that its optical and electronic oscillations are coupled to each other in a single device. The present frequency-stabilization scheme is best described indirectly by describing the laboratory apparatus used to demonstrate it. The apparatus (see figure) includes a COEO that generates a comb-like optical spectrum, the various frequency components of which interfere, producing short optical pulses. This spectrum is centered at a nominal wavelength of 1,560 nm. The spectrum separation of this comb is about 10 GHz, as determined primarily by the length of an optical loop and the bandpass filter in the microwave feedback loop. The optical loop serves as microwave resonator having a very high value of the resonance quality factor (Q). The optical frequency of MLL is then stabilized by locking it to an atomic transition as described below. The COEO contains a tunable 1-nm band-pass optical filter and a piezoelectric-transducer (PZT) drum over which a stretch of fiber is wound. The 1-nm-wide pass band of the filter provides coarse tuning to overlap the frequency comb with the atomic transition frequency. Controlled stretching of the fiber by means of the PZT drum can be used in conjunction with temperature control for locking the laser frequency. To reference to an atomic resonance at 780 nm in this demonstration setup, the optical output of the COEO at 1,560 nm is fed through an erbium-doped-fiber amplifier (EDFA) to a frequency doubler in the form of a periodically poled lithium niobate (PPLN) crystal. The frequency-doubled output is combined with the output of a separate frequency-stabilized diode laser at a photodetector. As described thus far, the two 780-nm laser subsystems are nominally independent of each other and can, therefore, operate at different frequencies. Hence, at the photodetector, the two laser beams interfere, so that the output of the photodetector includes a beat note (a component at the difference between the two laser frequencies).
A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.
Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability.
Multi-pixel transition-edge sensors (TESs), commonly referred to as 'hydras', are a type of position sensitive micro-calorimeter that enables very large format arrays to be designed without commensurate increase in the number of readout channels and associated wiring. In the hydra design, a single TES is coupled to discrete absorbers via varied thermal links. The links act as low pass thermal filters that are tuned to give a different characteristic pulse shape for x-ray photons absorbed in each of the hydra sub pixels. In this contribution we report on the experimental results from hydras consisting of up to 20 pixels per TES. We discuss the design trade-offs between energy resolution, position discrimination and number of pixels and investigate future design optimizations specifically targeted at meeting the readout technology considered for Lynx.
Acquisition of unsteady pressure using remote scanners can provide practical advantages over making the same measurements directly using flush-mounted pressure transducers. However, pneumatic distortion of the signal is introduced by the tubing between the sensing module and surface port. This typically limits the usefulness of such measurements to averaged, steady data only, restricting the application of pressure scanners for unsteady pressure measurements in the wind tunnel and flight-testing applications. In this work, unsteady pressure on the surface of a 1.75%-scale model of the NASA Space Launch System Block 1B Cargo vehicle was remotely measured at the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel using an ESP pressure scanner. Subsequent reconstruction using an empirically-tuned, Wiener-filtered inverse transfer function produced excellent agreement compared to nearby surface-mounted transducers within a usable bandwidth of approximately 500 Hz. Interactions between the launch vehicle and the support tower produced strong oscillations that were absent in the vehicle-alone configuration, and it is likely that the wake interaction leads to a resonant flow response when the launch tower is immediately downstream of the vehicle.
The Phase change material-based actively-tunable filter (P-ACTIVE, Dr. Hyun Jung Kim, the Principal Investigator / PI) project is a NASA Langley Research Center (LaRC)-led research endeavor that began as a NASA CIF (Center Innovation Fund) project in 2019. The goal of P-ACTIVE is to develop all-solid-state tunable optical filters that can serve as low-Size, Weight, and Power (SWaP) replacements to the ubiquitous filter wheel technology current in use, and serve as a starting point for completely new optical component technologies. By using materials commonly used in electronic memory devices, namely chalcogenide phase-change materials (PCMs), in conjunction with nanostructured surfaces with exotic, tailored optical responses (“metasurfaces”), the P-ACTIVE filters are able to tune their optical transmission/reflection behavior in real-time. Because of this new functionality, P-ACTIVE filters are highlighted for NASA science and space programs such as next generation Lidar, landing system (SLS) thermal monitoring, thermal imaging, imaging spectroscopy, and disaster monitoring (e.g., volcanic eruption observations from SmallSats). This document intends to serve as a compendium of the P-ACTIVE project. We begin by describing the project from background science and assume no prior knowledge of the subject. We then address experimental and theoretical results of P-ACTIVE device performance, as well as recent results obtained from the MISSE-14 mission related to space qualification of P-ACTIVE devices and constituent materials. We conclude with a prospective view of the P-ACTIVE technology, and discuss the potential for these filters and other similar metasurface devices to serve NASA’s mission.
This work will demonstrate the integration of sensor and system dynamic data and their appropriate models using an optimal filter to create a robust, adaptable, easily reconfigurable state (motion) estimation system. This state estimation system will clearly show the application of fundamental modeling and filtering techniques. These techniques are presented at a general, first principles level, that can easily be adapted to specific applications. An example of such an application is demonstrated through the development of an integrated GPS/INS navigation system. This system acquires both global position data and inertial body data, to provide optimal estimates of current position and attitude states. The optimal states are estimated using a Kalman filter. The state estimation system will include appropriate error models for the measurement hardware. The results of this work will lead to the development of a "black-box" state estimation system that supplies current motion information (position and attitude states) that can be used to carry out guidance and control strategies. This black-box state estimation system is developed independent of the vehicle dynamics and therefore is directly applicable to a variety of vehicles. Issues in system modeling and application of Kalman filtering techniques are investigated and presented. These issues include linearized models of equations of state, models of the measurement sensors, and appropriate application and parameter setting (tuning) of the Kalman filter. The general model and subsequent algorithm is developed in Matlab for numerical testing. The results of this system are demonstrated through application to data from the X-33 Michael's 9A8 mission and are presented in plots and simple animations.
Tunable mid-wave infrared (MWIR) filters are highly desirable in a wide variety of imaging and sensing, as the MWIR contains numerous spectral signatures. We fabricated spectrally-tunable Fabry-Perot bandpass filters operating across the MWIR by utilizing the phase-change material GeSbTe (GST) as a tunable cavity medium between distributed Bragg reflectors. The induced refractive index modulation of the GST increases the cavity’s optical path length, tuning the passband. Our filters have 300-nm spectral tunability, 60-75% transmission efficiencies, and 50-65 nm narrowband FWHMs (Q-factor 70-90). We demonstrate multispectral thermal imaging and dynamic gas sensing by matching the filter’s passband (~ 4.25μm) to a CO2 vibrational-absorption mode.
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter's performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
An Extended Kalman Filter is developed to estimate the linearized direct and indirect stiffness and damping force coefficients for bearings in rotor-dynamic applications from noisy measurements of the shaft displacement in response to imbalance and impact excitation. The bearing properties are modeled as stochastic random variables using a Gauss-Markov model. Noise terms are introduced into the system model to account for all of the estimation error, including modeling errors and uncertainties and the propagation of measurement errors into the parameter estimates. The system model contains two user-defined parameters that can be tuned to improve the filter s performance; these parameters correspond to the covariance of the system and measurement noise variables. The filter is also strongly influenced by the initial values of the states and the error covariance matrix. The filter is demonstrated using numerically simulated data for a rotor-bearing system with two identical bearings, which reduces the number of unknown linear dynamic coefficients to eight. The filter estimates for the direct damping coefficients and all four stiffness coefficients correlated well with actual values, whereas the estimates for the cross-coupled damping coefficients were the least accurate.
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).
Inductorless tuned circuit functions as filter, amplifier, or oscillator at radio frequencies. Circuit is based on two directly-coupled transistors operated at their transition frequency and fabricated as integrated circuit on single silicon chip.
In July, 2005 Deep Impact successfully impacted comet Tempel-1 and imaged the crater evolution. To achieve this, an onboard autonomous navigation system had to estimate the trajectory and maneuver the Impactor spacecraft into the comet's path. A similar system, operating on the Flyby spacecraft, calculated the impact location for imaging. At the heart of each autonomous navigation system is the attitude and gyro bias estimator using star trackers and gyros. The encounter geometry and timing placed stringent demands on attitude bias magnitude and drift calling for sequenced tuning of the respective filters. This paper describes the attitude and gyro bias estimator algorithms, the estimator flight performance and particular challenges overcome by the team leading up to a spectacular encounter.