Meander-DGS Effect on Electromagnetic Bandgap Structure for Power/Ground Noise Suppression in High-Speed Integrated Circuit Packages and PCBs

In this paper, we present the impact of a meander-shaped defected ground structure (MDGS) on the slow-wave characteristics of a lowest-order passband and a low cutoff frequency of the first stopband of an electromagnetic bandgap (EBG) structure for power/ground noise suppression in high-speed integrated circuit packages and printed circuit boards (PCBs). A semi-analytical method is presented to rigorously analyze the MDGS effect. In the analytical method, a closed-form expression for a low cutoff frequency of the MDGS-EBG structure is extracted with an effective characteristic impedance and a slow-wave factor. The proposed analytical method enables the fast analysis of the MDGS-EBG structure so that it can be easily optimized. The analysis of the MDGS effect revealed that the low cutoff frequency increases up to approximately 19% while comparing weakly and strongly coupled MDGSs. It showed that the miniaturization of the MDGS-EBG structure can be achieved. It was experimentally verified that the low cutoff frequency is reduced from 2.54 GHz to 2.00 GHz by decreasing the MDGS coupling coefficient, which is associated with the miniaturization of the MDGS-EBG structure in high-speed packages and PCBs.

A System for Measurement and Analysis of Aircraft Noise Impacts

The Metroplex Overflight Noise Analysis (MONA) project seeks to measure, analyze, and archive the ground noise generated by aircraft overflights and to provide accurate and actionable data for a variety of different purposes. On the one hand, experimental datasets collected and processed by the MONA system can serve as an openly-available database for validation and verification (V&V) of improved noise prediction methods. On the other, study conclusions derived from both the experimental and computational data can serve to inform technical discussions and options involving aircraft noise, aircraft routes, and the potential impacts of the FAA’s NextGen procedure changes on overflown communities at varying distances from the airport. Given the complex interdependencies between the noise levels perceived on the ground and the air-traffic patterns that generate the aircraft noise, a secondary goal of the MONA project is to share, through compelling visualizations, key results with broad communities of stakeholders to help generate a common understanding and reach better decisions more quickly. In this paper, we focus on the description of the MONA system architecture, its design, and its current set of capabilities. Subsequent publications will focus on the results we are obtaining though the use of the MONA system.

Filtering ground noise from LiDAR returns produces inferior models of forest aboveground biomass

Airborne LiDAR has become an essential data source for large-scale, high-resolution modeling of forest biomass and carbon stocks, enabling predictions with much higher resolution and accuracy than can be achieved using optical imagery alone. Ground noise filtering -- that is, excluding returns from LiDAR point clouds based on simple height thresholds -- is a common practice meant to improve the 'signal' content of LiDAR returns by preventing ground returns from masking useful information about tree size and condition contained within canopy returns. Although this procedure originated in LiDAR-based estimation of mean tree and canopy height, ground noise filtering has remained prevalent in LiDAR pre-processing, even as modelers have shifted focus to forest aboveground biomass (AGB) and related characteristics for which ground returns may actually contain useful information about stand density and openness. In particular, ground returns may be helpful for making accurate biomass predictions in heterogeneous landscapes that include a patchy mosaic of vegetation heights and land cover types. In this paper, we applied several ground noise filtering thresholds while mapping two study areas in New York (USA), one a forest-dominated area and the other a mixed-use landscape. We observed that removing ground noise via any height threshold systematically biases many of the LiDAR-derived variables used in AGB modeling. By fitting random forest models to each of these predictor sets, we found that that ground noise filtering yields models of forest AGB with lower accuracy than models trained using predictors derived from unfiltered point clouds. The relative inferiority of AGB models based on filtered LiDAR returns was much greater for the mixed land-cover study area than for the contiguously forested study area. Our results suggest that ground filtering should be avoided when mapping biomass, particularly when mapping heterogeneous and highly patchy landscapes, as ground returns are more likely to represent useful 'signal' than extraneous 'noise' in these cases.

Water vapour radiometry in geodetic very long baseline interferometry telescopes: assessed through simulations

The accuracy of geodetic Very Long Baseline Interferometry (VLBI) is affected by water vapour in the atmosphere in terms of variations in the signal propagation delay at the different stations. This “wet” delay may be estimated directly from the VLBI data, as well as from independent instruments, such as collocated microwave radiometers. Rather than having stand-alone microwave radiometers we have, through simulations, evaluated the possibility to use radiometric data from the VLBI receiver in the VGOS telescopes at the Onsala Space Observatory. The advantage is that the emission from water vapour, as sensed by the radiometer, originates from the same atmospheric volume that delays the VLBI signal from the extra-galactic object. We use simulations of the sky brightness temperature and the wet delay together with an assumption of a root-mean-square (rms) noise of the receiver of 1 K, and observations evenly spread between elevation angles of 10$$^\circ $$ ∘ –90$$^\circ $$ ∘ . This results in an rms error of the estimated equivalent zenith wet delay of the order of 3 mm for a one frequency algorithm, used under cloud free conditions, and 4 mm for a two frequency algorithm, used during conditions with liquid water clouds. The results exclude rainy conditions when the method does not work. These errors are reduced by a factor of 3 if the receiver error is 0.1 K meaning that the receivers’ measurements of the sky brightness temperature is the main error source. We study the impact of ground-noise pickup by using a model of an existing wideband feed. Taking the algorithm uncertainty and the ground noise pickup into account we conclude that the method presented will be useful as an independent estimate of the wet delay to assess the quality of the wet delays and linear horizontal gradients estimated from the VLBI data themselves.

Advanced procedure noise model validation using Seattle International Airport noise monitor networks

Advanced operational flight procedures that utilize modifications to thrust, airspeed, altitude, and configuration can be implemented to mitigate noise impacts for communities surrounding airports. Evaluating and designing such procedures requires accurate modeling of the aircraft performance, source noise, and atmospheric propagation of the source noise to the ground. Modeling frameworks to assess advanced procedures have been developed but must be validated to ensure their results are reasonable. This paper presents validation of such noise models using a network of ground noise monitoring data at Seattle-Tacoma International airport and ADS-B operational radar flight profiles from the OpenSky database. Modeled noise from operational flights of several aircraft types are shown to be consistent with noise monitor data when reasonable flap settings and atmospheric corrections for the actual weather at the time of flight are used. Discrepancies that exist between the modeled and measured noise results are identified to determine where current noise modeling methods must be improved to accurately represent all relevant noise sources.

Operational noise optimization of aircraft approaches - Initial findings

As the pilots slow the aircraft down and extend flaps and landing gear in preparation for landing the characteristics of the aircraft as a noise source changes. In the OPNOP project, the possibility to use this variation in noise generation to minimize noise at a specified location is examined. Such analysis requires an increased understanding about aircraft noise generation as the aircraft changes configuration and speed during the approach, where theoretical models available can be overly simplistic and of little use for this purpose. Using flight data from 113 actual Airbus A321 flights, and corresponding noise measurements on the ground, this study reports on the initial findings forming the foundation on which further analysis will be conducted. Intermediary findings relate to: a comparison between models and actual measurements, the distance variability to the runway for various flap selections and extension of the landing gear as well as a comparison between flight data and on-ground noise measurements. Captured data suggest that it should be possible to use speed and configuration recommendations to reduce noise over selected approach areas. Future research will include scenario generation and incorporate flight data from an earlier study to increase validity.