Publications

Reducing thunderstorm-related air traffic delays in congested airspace has become a major objective of the FAA, especially given the recent growth in convective delays. In 2000 and 2001, the key new initiative for reducing these convective weather delays was "strategic" traffic flow management (TFM). Users were given 2-, 4-, and 6-hour collaborative convective weather forecasts, and collaborative traffic routing plans were established via telecons attended by Air Traffic Control (ATC) and airline traffic managers. This "strategic" approach led to difficulties during a large fraction of the weather events because it was not possible to generate forecasts of convective weather at time horizons between 2 and 6 hours that were accurate enough to assess impacts on routes and capacity, and thereby accomplish effective TFM. During convective weather events, traffic managers tend to focus on tactical TFM [Huberdeau, 2004], yet they had relatively inaccurate current weather information and tactical forecasts. The Corridor Integrated Weather System (CIWS) demonstration began in 2001. The objectives of the demonstration are to provide improved tactical air traffic management (ATM) decision support, via improved real time 3D products and accurate short-term convective weather forecasts, and to determine if this support is an operationally useful complement to "strategic" TFM. The current focus of the CIWS initiative is the highly congested airspace containing the Great Lakes and Northeast corridors, since that region offers the greatest potential for delay reduction benefits. In this paper, we describe the current status of CIWS, including initial operational results of Air Traffic Control (ATC) and airline use of the CIWS weather products. We begin with some CIWS background, describing the motivation for the program, the role of CIWS products in the overall convective weather planning process, and the functional domains in which CIWS products can provide operationally significant benefits. We then review the current CIWS capabilities, spatial coverage, sensors used, products, operational users, and integration with ATM systems. Next the detailed CIWS operational benefits study carried out in 2003 is summarized. Finally, we discuss the FAA plans for CIWS and near term enhancements to the system.

In this paper, we summarize contemporary approaches to quantifying convective weather delay reduction benefits. We outline a program to develop a significantly improved capability that can be used to assess benefits of specific systems. This program may potentially accomplish weather impact normalization for studies of National Airspace System (NAS) performance in handling convective weather. Benefits quantification and NAS performance assessment have become very important topics for the aviation weather community. In an era of significant federal government and airline budget austerity for civil aviation investments, it is essential to quantitatively demonstrate delay reduction benefits of improved weather decision support systems. Major FAA initiatives stress the importance of quantitative system performance metrics that are related to aviation weather. For example, the new FAA Air Traffic Organization (ATO) and the FAA Flight Plan 2004-08 both have quantitative performance metrics that are closely related to reducing convective weather delays. The Flight Plan metrics include: "Improving the percentage of all flights arriving within 15 minutes of schedule at the 35 OEP airports by 7%, as measured from the FY2000-02 baseline, through FY08," and "Maintaining average en route travel times among the eight major metropolitan areas." The ATO metrics include the percentage of on time gate arrivals and the fraction of departures that are delayed greater than 40 minutes. However, these metrics currently do not account for the differences in convective weather severity and changes in the NAS. The dramatic increase in convective season delays in 2004 (Figure 1) due to a combination of severe weather, increases in overall demand, and specific airport issues has demonstrated that one needs to consider these other factors. Approaches to delay reduction quantification that were viewed as successful and valid several years ago are no longer considered to be adequate by either by the FAA investment analysis branch or by the Office of Management and Budget (OMB). The paper proceeds as follows. We first discuss at some length the mechanisms by which convective weather delay occurs in the NAS and highlight challenges in delay reduction assessment. We consider this to be very important since one needs to understand how the system operates if one is to design an effective, accurate performance assessment system. We then consider benefits quantification based on feedback from experienced users of a system. Feedback on "average" benefits from a system at the end of a test period was used to generate delay reduction estimates for the Integrated Terminal Weather System (ITWS) and the Weather and Radar Processor (WARP). This end-of-season interview approach was not viable in highly congested en route airspace. Hence, a new approach was developed for Corridor Integrated Weather System (CIWS) benefits assessment that uses real time observations of product usage during convective weather events coupled with in depth analysis of specific cases. Next, we discuss the problems that arise when one attempts to quantify delay reduction benefits by comparing flight delays before and after the Integrated Terminal Weather System (ITWS) system was deployed at Atlanta Hartsfield International Airport (ATL). This seemingly simple approach has proven very difficult in practice because the convective weather events in the different time periods are virtually never identical and because other aspects of the NAS may also have changed (e.g., user demand, fleet mix, and other systems that impact convective weather delays). It has become clear that one needs a quantitative model for the NAS that would permit adjustment of measured delay data to account at least for the differences in convective weather and changes in user demand (i.e., flight scheduling). The paper concludes with recommendations for measuring near term benefits of various classes of convective weather decision support systems.

Major airlines and FAA Traffic Flow Managers alike would prefer to plan their flight routes around convective weather and thereby avoid the tactical maneuvering that results when unforecasted thunderstorms occur. Strategic planning takes place daily and 2-6 hr forecasts are utilized, but these early plans remain unaltered in only the most predictable of convective weather scenarios. More typically, the ATC System Command Center and the Air Route Traffic Control Centers together with airline dispatchers will help flights to utilize jet routes that remain available within regions of convection, or facilitate major reroutes around convection, according to the available "playbook" routes. For this tactical routing in the presence of convective weather to work, both a precise and timely shared picture of current weather is required as well as an accurate, reliable short term (0-2 hr) forecast. This is crucial to containing the system-wide and airport-specific delays that are so prevalent in the summer months (Figure 1), especially as traffic demands approach full capacity at the pacing airports. This paper describes the Tactical 0-2 hr Convective Weather Forecast (CWF) algorithm developed by the MIT Lincoln Laboratory for the FAA, principally sponsored by the Aviation Weather Research Program (AWRP). This CWF technology is currently being utilized in both the Integrated Terminal Weather System (ITWS; Wolfson et al., 2004) and the Corridor Integrated Weather System (CIWS; Evans et al., 2004) proof-of-concept demonstrations. Some of this technology is also being utilized in the National Convective Weather Forecast from the Aviation Weather Center (Megenhardt, 2004), the NCAR Autonowcaster (Saxen et al., 2004), and in various private-vendor forecast systems.

Wake vortices are a by-product of lift generated by aircraft. The vortices from the wings and other lift surfaces such as flaps spin off and trail behind an aircraft (see Figure 1). These vortices can be a hazard to other aircraft, especially lighter aircraft that are following at low altitude. For this reason, numerous air traffic control standards require increased aircraft separation when wake vortex avoidance is a concern. These separation standards provide the required safety: there has never been a fatal accident in the U.S. due to wake vortices when wake vortex separations were provided by air traffic controllers. Wake vortex behavior is strongly dependent on atmospheric conditions, giving rise to the possibility that wake behavior can be predicted with enough precision to allow reduced use of wake vortex avoidance separations. Because vortices can not be seen, and their location and strength are not currently known or predicted, separation standards and air traffic procedures are designed to account for the worst case wake behavior. Because of this, the imposed aircraft separations are larger than required much of the time, reducing terminal capacity and causing increased traffic delay. If procedures or technologies can be developed to reduce the use of wake avoidance separations, terminal area delay reduction may be achieved. A prototype wind dependent wake separation system is operating in Frankfurt, Germany for arrivals into closely spaced parallel runways. The system uses wind prediction at the surface to determine when separation for wake vortex avoidance must be used and when the extra separation does not need to be used [Konopka, 2001][Frech, et al., 2002]. This led the FAA to ask the question: does the wind prediction algorithm used in Frankfurt, or perhaps another algorithm, have sufficient performance to consider it for possible use in the US for a closely spaced parallel runway departure system? This paper reports on a research effort to answer that question. This is part of a larger FAA and NASA research effort [Lang et al., 2003].

An important concern in speaker recognition is the performance degradation that occurs when speaker models trained with speech from one type of channel are subsequently used to score speech from another type of channel, known as channel mismatch. This paper investigates the relative performance of two different spectral subtraction methods for additive noise compensation in the context of speaker verification. The first method, termed "soft" spectral subtraction, is performed in the spectral domain on the |DFT|^2 values of the speech frames while the second method, termed "hard" spectral subtraction, is performed on the Mel-filter energy features. It is shown through both an analytical argument as well as a simulation that soft spectral subtraction results in a higher signal-to-noise ratio in the resulting Mel-filter energy features. In the context of Gaussian mixture model-based speaker verification with additive noise in testing utterances, this is shown to result in an equal error rate improvement over a system without spectral subtraction of approximately 7% in absolute terms, 21% in relative terms, over an additive white Gaussian noise range of 5-25 dB.

The integration of Remotely Piloted Vehicles (RPVs) into civil airspace will require new methods of ensuring traffic avoidance. This paper discusses issues affecting requirements for RPV traffic avoidance systems and describes the safety evaluation process that the international community has deemed necessary to certify such systems. Alternative methods for RPVs to perform traffic avoidance are discussed, including the potential use of new see-and- avoid sensors or the Traffic Alert and Collision Avoidance System (TCAS). Concerns that must be addressed to allow the use of TCAS on RPVs are presented. The paper then details the safety evaluation process that is being implemented to evaluate the safety of TCAS on Global Hawk. The same evaluation process can be extended to other RPVs and traffic avoidance systems for which thorough safety analyses will also be required.

Utilizing the largest available data sets for the observed taxonomic and albedo distributions of the near-Earth object population, we model the bias-corrected population. Diameter-limited fractional abundances of the taxonomic complexes are A-0.2%; C-10%, D-17%, O-0.5%, Q-14%, R-0.1%, S-22%, U-0.4%, V-1%, X-34%. In a diameter-limited sample, ~30% of the NEO population has jovian Tisserand parameter less than 3, where the D-types and X-types dominate. The large contribution from the X-types is surprising and highlights the need to better understand this group with more albedo measurements. Combining the C, D, and X complexes into a "dark" group and the others into a "bright" group yields a debiased darkto- bright ratio of ~1.6. Overall, the bias-corrected mean albedo for the NEO population is 0.14 +/-0.02, for which an H magnitude of 17.8 +/-0.1 translates to a diameter of 1 km, in close agreement with Morbidelli et al. Coupling this bias corrected taxonomic and albedo model with the H magnitude dependent size distribution of yields a diameter distribution with 1090 +/-180 NEOs with diameters larger than 1 km. As of 2004 June, the Spaceguard Survey has discovered 56% of the NEOs larger than 1 km. Using our size distribution model, and orbital distribution of we calculate the frequency of impacts into the Earth and the Moon. Globally destructive collisions (~10 ^21 J) of asteroids 1 km or larger strike the Earth once every 0.60 +/-0.1 Myr on average. Regionally destructive collisions with impact energy greater than 4 x 10 ^18 J (~200 m diameter) strike the Earth every 56,000 +/-6000 yr. Collisions in the range of the Tunguska event (4-8 x 10^16 J) occur every 2000-3000 yr. These values represent the average time between randomly spaced impacts; actual impacts could occur more or less closely spaced solely by chance. As a verification of these impact rates, the crater production function of Shoemaker et al. has been updated by combining this new population model with a crater formation model to find that the observed crater production function on both the Earth and Moon agrees with the rate of crater production expected from the current population of NEOs.

This report develops robust signal processing architectures and algorithms specifically designed to achieve multi-aperture coherence on transmit and receive. A key feature of our approach is the use of orthogonal radar waveforms that allow the monostatic and bistatic target returns to be separated at each receiver's matched filter output. By analyzing these returns, we may determine the appropriate transmit times and phases in order to cohere the various radar apertures using both narrowband and wideband waveforms. This process increases the array gain on receive to N2 instead of N for the single transmitter case. Furthermore, when hll coherence on transmit is achieved, the array gain is N3. The performance of our coherence algorithms is quantified using Monte Carlo simulations and compared to the Cramer-Rao lower bound. A computational complexity study shows that our aperture coherence algorithms are suitable for a realtime implementation on an SGI Origin 3000 multi-processor computer.

We establish a new worst-case upper bound on the Membership problem: We present a simple algorithm that is able to always achieve Agreement on Views within a single message latency after the final network events leading to stability of the group become known to the membership servers. In contrast, all of the existing membership algorithms may require two or more rounds of message exchanges. Our algorithm demonstrates that the Membership problem can be solved simpler and more efficiently than previously believed. By itself, the algorithm may produce disagreement (that is, inconsistent, transient views) prior to the "final" view. Even though this is allowed by the problem specification, such views may create overhead at the application level, and are therefore undesirable. We propose a new approach for designing group membership services in which our algorithm for reaching Agreement on Views is combined with a filter-like mechanism for reducing disagreements. This approach can use the mechanisms of existing algorithms, yielding the same multi-round performance as theirs. However, the power of this approach is in being able to use other mechanisms. These can be tailored to the specifics of the deployment environments and to the desired combinations of the speed of agreement vs. the amount of preceding disagreement. We describe one mechanism that keeps the combined performance to within a single-round, and sketch another two.

Examples are advances in ground moving target indicator (GMTI) processing, space-time adaptive processing (STAP), target discrimination, and electronic counter-countermeasures (ECCM). All these advances have improved the capabilities of radar sensors. Major improvements expected in the next several years will come from exploiting collaborative network-centric architectures to leverage synergies among individual sensors. Such an approach has become feasible as a result of major advances in network computing, as well as communication technologies in both wireless and fiber networks. The exponential growth of digital technology, together with highly capable networks, enable in-depth exploitation of sensor synergy, including multi-aspect sensing. New signal processing algorithms exploiting multi-sensor data have been demonstrated in non-real-time, achieving improved performance against surface mobile targets by leveraging high-speed sensor networks. The paper demonstrates a significant advancement in exploiting complex ground moving target indicator (GMTI) and synthetic aperture radar (SAR) data to accurately geo-locate and identify mobile targets.