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At least 55 records · Page 3

Application of Swept-Sine Excitation for Acoustic Impedance Education

The NASA Langley Normal Incidence Tube (NIT) and Grazing Flow Impedance Tube (GFIT) are regularly employed to characterize the frequency response of acoustic liners through the eduction of their specific acoustic impedance. Both test rigs typically use an acoustic source that produces sine wave signals at discrete frequencies (Stepped-Sine) to educe the impedance. The current work details a novel approach using frequency-swept sine waveforms normalized to a constant sound pressure level for excitation. Determination of the sound pressure level and phase from microphone measurements acquired using swept-sine excitation is performed using a modified Vold-Kalman order tracking filter. Four acoustic liners are evaluated in the NIT and GFIT with both stepped-sine and swept-sine sources. Using these two methods, the educed impedance spectra are shown to compare favorably. However, the new (Swept-Sine) approach provides much greater frequency resolution in less time, allowing the acoustic liner properties to be studied in much greater detail.

Howerton, Brian M.↗

Identification and Computation of Individual Propeller Acoustics of the Joby Aviation Aircraft

The individual propeller sources of the Joby Aviation aircraft are separated using an order tracking filter on measurement data and computed using high- fidelity computational fluid dynamics (CFD) to quantify the relative contributions to the total noise. Computational results are verified against experimental data for hover and steady level flight at 60 knots and demonstrate very good agreement of both overall sound pressure level magnitude and directivity. The propeller source separation for hover shows good agreement between the methods except for the inboard propellers, and it is expected that the assumptions in the CFD model do not accurately capture the flight test condition. Both methods are able to separate the higher tonal levels generated by the tail propellers due to the aerodynamic interaction. Overall, considering the discrepancies between the CFD model and flight test, the agreement in Vold-Kalman-filtered results and prediction yields confidence that the separation method is successful.

eVTOL↗

In-pixel integration of signal processing and AI/ML based data filtering for particle tracking detectors

We present the first physical realization of in-pixel signal processing with integrated AI-based data filtering for particle tracking detectors. Building on prior work that demonstrated a physics-motivated edge-AI algorithm suitable for ASIC implementation, this work marks a significant milestone toward intelligent silicon trackers. Our prototype readout chip performs real-time data reduction at the sensor level while meeting stringent requirements on power, area, and latency. The chip is taped-out in 28nm TSMC CMOS bulk process, which has been shown to have sufficient radiation hardness for particle experiments. This development represents a key step toward enabling fully on-detector edge AI, with broad implications for data throughput and discovery potential in high-rate, high-radiation environments such as the High-Luminosity LHC.

Parpillon, Benjamin [Fermilab; Illinois U., Chicag↗

In-Time UAV Flight-Trajectory Estimation and Tracking Using Bayesian Filters

Rapid increase of UAV operation in the next decade in areas of on-demand delivery, medical transportation services, law enforcement, traffic surveillance and several others pose potential risks to the low altitude airspace above densely populated areas. Safety assessment of airspace demands the need for a novel UAV traffic management (UTM) framework for regulation and tracking of the vehicles. Particularly for low-altitude UAV operations, quality of GPS measurements feeding into the UAV is often compromised by loss of communication link caused by presence of trees or tall buildings in proximity to the UAV flight path. Inaccurate GPS locations may yield to unreliable monitoring and inaccurate prognosis of remaining battery life and other safety metrics which rely on future expected trajectory of the UAV. This work therefore proposes a generalized monitoring and prediction methodology for autonomous UAVs using in-time GPS measurements. Firstly, a typical 4D smooth trajectory generation technique from a series of waypoint locations with associated expected times-of-arrival based on B-spline curves is presented. Initial uncertainty in the vehicle's expected cruise velocity is quantified to compute confidence intervals along the entire flight trajectory using error interval propagation approach. Further, the generated planned trajectory is considered as the prior knowledge which is updated during its flight with incoming GPS measurements in order to estimate its current location and corresponding kinematic profiles. Estimation of position is denoted in dicrete state-space representation such that position at a future time step is derived from position and velocity at current time step and expected velocity at the future time step. A linear Bayesian filtering algorithm is employed to efficiently refine position estimation from noisy GPS measurements and update the confidence intervals. Further, a dynamic re-planning strategy is implemented to incorporate unexpected detour or delay scenarios. Finally, critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified, and potential solutions are discussed at the end of the paper. The entire monitoring framework is demonstrated on real UAV flight experiments conducted at the NASA Langley Research Center.

Banerjee, Portia↗

Carrier tracking by smoothing filter can improve symbol SNR

The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (CNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

Hurd, W. J.↗

Carrier tracking by smoothing filter improves symbol SNR

The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (SNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.

Pomalaza-Raez, Carlos A.↗

Motion detection, novelty filtering, and target tracking using an interferometric technique with a GaAs phase conjugate mirror

A method and apparatus is disclosed for detecting and tracking moving objects in a noise environment cluttered with fast-and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photo-refractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the inter-ferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Cheng, Li-Jen↗

Motion detection, novelty filtering, and target tracking using an interferometric technique with GaAs phase conjugate mirror

A method and apparatus for detecting and tracking moving objects in a noise environment cluttered with fast- and slow-moving objects and other time-varying background. A pair of phase conjugate light beams carrying the same spatial information commonly cancel each other out through an image subtraction process in a phase conjugate interferometer, wherein gratings are formed in a fast photorefractive phase conjugate mirror material. In the steady state, there is no output. When the optical path of one of the two phase conjugate beams is suddenly changed, the return beam loses its phase conjugate nature and the interferometer is out of balance, resulting in an observable output. The observable output lasts until the phase conjugate nature of the beam has recovered. The observable time of the output signal is roughly equal to the formation time of the grating. If the optical path changing time is slower than the formation time, the change of optical path becomes unobservable, because the index grating can follow the change. Thus, objects traveling at speeds which result in a path changing time which is slower than the formation time are not observable and do not clutter the output image view.

Cheng, Li-Jen↗

Synchronous response modelling and control of an annular momentum control device

Research on the synchronous response modelling and control of an advanced Annular Momentun Control Device (AMCD) used to control the attitude of a spacecraft is described. For the flexible rotor AMCD, two sources of synchronous vibrations were identified. One source, which corresponds to the mass unbalance problem of rigid rotors suspended in conventional bearings, is caused by measurement errors of the rotor center of mass position. The other sources of synchronous vibrations is misalignment between the hub and flywheel masses of the AMCD. Four different control algorithms were examined. These were lead-lag compensators that mimic conventional bearing dynamics, tracking notch filters used in the feedback loop, tracking differential-notch filters, and model-based compensators. The tracking differential-notch filters were shown to have a number of advantages over more conventional approaches for both rigid-body rotor applications and flexible rotor applications such as the AMCD. Hardware implementation schemes for the tracking differential-notch filter were investigated. A simple design was developed that can be implemented with analog multipliers and low bandwidth, digital hardware.

Hockney, Richard↗

Sequential filtering applied to the determination of tracking station locations

The extended sequential filter has been applied to the problem of dynamically determining the geocentric coordinates of two laser satellite tracking stations. This filter provides significant advantages over the classical batch methods through (1) fewer iterations required for convergence, (2) wider radius of convergence, and (3) availability of the parameter estimate evolution. Processing the data sequentially readily identifies the data arcs required to minimize the effects of geopotential model errors. By means of the Smithsonian standard earth 2 and the Goddard earth model 1 geopotentials to reduce laser range observations of the Beacon Explorer-C satellite, it is demonstrated that a two-pass arc is optimal for estimating the height of one station and all coordinates of the second station while minimizing the effect of geopotential model error. These two-pass estimates are in good agreement with other determinations that utilize considerably more data as well as different satellites.

Schutz, B. E.↗

Advanced data assimilation in strongly nonlinear dynamical systems

Advanced data assimilation methods are applied to simple but highly nonlinear problems. The dynamical systems studied here are the stochastically forced double well and the Lorenz model. In both systems, linear approximation of the dynamics about the critical points near which regime transitions occur is not always sufficient to track their occurrence or nonoccurrence. Straightforward application of the extended Kalman filter yields mixed results. The ability of the extended Kalman filter to track transitions of the double-well system from one stable critical point to the other depends on the frequency and accuracy of the observations relative to the mean-square amplitude of the stochastic forcing. The ability of the filter to track the chaotic trajectories of the Lorenz model is limited to short times, as is the ability of strong-constraint variational methods. Examples are given to illustrate the difficulties involved, and qualitative explanations for these difficulties are provided. Three generalizations of the extended Kalman filter are described. The first is based on inspection of the innovation sequence, that is, the successive differences between observations and forecasts; it works very well for the double-well problem. The second, an extension to fourth-order moments, yields excellent results for the Lorenz model but will be unwieldy when applied to models with high-dimensional state spaces. A third, more practical method--based on an empirical statistical model derived from a Monte Carlo simulation--is formulated, and shown to work very well. Weak-constraint methods can be made to perform satisfactorily in the context of these simple models, but such methods do not seem to generalize easily to practical models of the atmosphere and ocean. In particular, it is shown that the equations derived in the weak variational formulation are difficult to solve conveniently for large systems.

Miller, Robert N.↗

Digital accumulators in phase and frequency tracking loops

Results on the effects of digital accumulators in phase and frequency tracking loops are presented. Digital accumulators or summers are used extensively in digital signal processing to perform averaging or to reduce processing rates to acceptable levels. For tracking the Doppler of high-dynamic targets at low carrier-to-noise ratios, it is shown through simulation and experiment that digital accumulators can contribute an additional loss in operating threshold. This loss was not considered in any previous study and needs to be accounted for in performance prediction analysis. Simulation and measurement results are used to characterize the loss due to the digital summers for three different tracking loops: a digital phase-locked loop, a cross-product automatic frequency tracking loop, and an extended Kalman filter. The tracking algorithms are compared with respect to their frequency error performance and their ability to maintain lock during severe maneuvers at various carrier-to-noise ratios. It is shown that failure to account for the effect of accumulators can result in an inaccurate performance prediction, the extent of which depends highly on the algorithm used.

Hinedi, Sami↗

Linear minimum variance filters applied to carrier tracking

A new approach is taken to the problem of tracking a fixed amplitude signal with a Brownian-motion phase process. Classically, a first-order phase-lock loop (PLL) is used; here, the problem is treated via estimation of the quadrature signal components. In this space, the state dynamics are linear with white multiplicative noise. Therefore, linear minimum-variance filters, which have a particularly simple mechanization, are suggested. The resulting error dynamics are linear at any signal/noise ratio, unlike the classical PLL. During synchronization, and above threshold, this filter with constant gains degrades by 3 per cent in output rms phase error with respect to the classical loop. However, up to 80 per cent of the maximum possible noise improvement is obtained below threshold, where the classical loop is nonoptimum, as demonstrated by a Monte Carlo analysis. Filter mechanizations are presented for both carrier and baseband operation.

Gustafson, D. E.↗

High resolution vertical profiles of wind, temperature and humidity obtained by computer processing and digital filtering of radiosonde and radar tracking data from the ITCZ experiment of 1977

Results are presented from computer processing and digital filtering of radiosonde and radar tracking data obtained during the ITCZ experiment when coordinated measurements were taken daily over a 16 day period across the Panama Canal Zone. The temperature relative humidity and wind velocity profiles are discussed.

Danielson, E. F.↗

A superconducting time-variant filtering system.

Description of a laboratory test facility for studying the tracking capabilities of a superconducting time-varying filter system. An RF signal from an antenna is amplified and fed to a mixer; the IF signal modulates an optical diode, and the emitted light is directed through an optical system onto a high-purity high-resistance semiconductor terminating a quarter-wavelength stub in a lead-plated superconducting cavity. The resulting perturbation in the cavity resonant frequency is proportional to the signal modulation present in the light beam. The narrow-band superconducting cavity is thereby acting as a time-variant filter that tracks the instantaneous signal modulation. SNR improvement on the order of 25 dB can be obtained due to the noise rejection characteristics of such a modulation tracking filter.

Arndt, G. D.↗