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A method for generating a minimum-fuel, fixed-range, fixed-time-of-arrival flight path in an on-board flight management system computer for commercial aircraft is described. It is shown that up to 6% of the fuel otherwise used can be saved by means of this capability, despite time-of-arrival delays of up to 30 min, by a medium-range, tri-jet transport aircraft.
We present a novel data-driven approach for prediction of the estimated time of arrival (ETA) of aircraft in the terminal area via the implementation of a Random Forest regression model. The model uses data fused from a number of sources (flight track, weather, flight plan information, etc.) and provides predictions for the remaining flight time for aircraft landing at Dallas/Fort Worth (DFW) International Airport. The predictions are made when the aircraft is at a distance of 200-miles from the airport. The results show that the model is able to predict estimated time of arrival to within ± 5 min for 90% of the flights in the test data with the mean absolute error being lower at 145 seconds. This paper covers the entire pipeline of data collection, preprocessing, setup and training of the ML model, and the results obtained for DFW.
Position surveillance using one active ranging/communication satellite and the time-of-arrival of signals from an independent satellite was shown to be feasible and practical. A towboat on the Mississippi River was equipped with a tone-code ranging transponder and a receiver tuned to the timing signals of the GOES satellite. A similar transponder was located at the office of the towing company. Tone-code ranging interrogations were transmitted from the General Electric Earth Station Laboratory through ATS-6 to the towboat and to the ground truth transponder office. Their automatic responses included digital transmissions of time-of-arrival measurements derived from the GOES signals. The Earth Station Laboratory determined ranges from the satellites to the towboat and computed position fixes. The ATS-6 lines-of-position were more precise than 0.1 NMi, 1 sigma, and the GOES lines-of-position were more precise than 1.6 NMi, 1 sigma. High quality voice communications were accomplished with the transponders using a nondirectional antenna on the towboat. The simple and effective surveillance technique merits further evaluation using operational maritime satellites.
Methods for evaluating and implementing air traffic management tools and approaches for managing and avoiding an air traffic incident before the incident occurs. A first system receives parameters for flight plan configurations (e.g., initial fuel carried, flight route, flight route segments followed, flight altitude for a given flight route segment, aircraft velocity for each flight route segment, flight route ascent rate, flight route descent route, flight departure site, flight departure time, flight arrival time, flight destination site and/or alternate flight destination site), flight plan schedule, expected weather along each flight route segment, aircraft specifics, airspace (altitude) bounds for each flight route segment, navigational aids available. The invention provides flight plan routing and direct routing or wind optimal routing, using great circle navigation and spherical Earth geometry. The invention provides for aircraft dynamics effects, such as wind effects at each altitude, altitude changes, airspeed changes and aircraft turns to provide predictions of aircraft trajectory (and, optionally, aircraft fuel use). A second system provides several aviation applications using the first system. Several classes of potential incidents are analyzed and averted, by appropriate change en route of one or more parameters in the flight plan configuration, as provided by a conflict detection and resolution module and/or traffic flow management modules. These applications include conflict detection and resolution, miles-in trail or minutes-in-trail aircraft separation, flight arrival management, flight re-routing, weather prediction and analysis and interpolation of weather variables based upon sparse measurements. The invention combines these features to provide an aircraft monitoring system and an aircraft user system that interact and negotiate changes with each other.
A digital avionics system referred to as STOLAND has been test-flown in the NASA CV-340 to obtain performance data for time-controlled guidance in the manual flight director mode. The advanced system components installed in the cockpit included an electronic attitude director indicator and an electronic multifunction display. Navigation guidance and control computations were all performed in the digital computer. Approach paths were flown which included a narrow 180-deg turn and a 1-min, 5-deg straight-in approach to the 30-m altitude go-around point. Results are presented for 20 approaches: (1) blended radio/inertial navigation using TACAN and a microwave scanning beam landing guidance system (MODILS) permitted a smooth transition from area navigation (TACAN) to precision terminal navigation (MODILS), (2) guidance system (flight director) performance measured at an altitude of 30.5 m was within that prescribed for category II CTOL operations on a standard runway, and (3) time of arrival at a point about 2 mi from touchdown was about 4 sec plus or minus sec later than the computed nominal arrival time.
The time of arrival at ATS 6 of substorm-associated energetic proton flux enhancements has been examined as a function of both energy and pitch angle by using electron-proton spectrometer data. The protons exhibit energy dispersion with the particles with the highest energy arriving first. This has generally been interpreted as evidence that these particles have gradient- and curvature-drifted to the spacecraft from an acceleration region on the nightside. In the evening quadrant, proton enhancements at 90 deg pitch angle arrived at the spacecraft prior to those at small pitch angles. However, on the dayside the increase occurs first at the smallest pitch angle (about 30 degrees). The difference between the arrival times of the 30 deg and 90 deg protons increases for more westward local times. For the highest energy range observed, drifting protons are rarely seen at large pitch angles. These observations place severe restrictions on the simple drift models. Since the pitch angle dependence of the particle drift velocity is a field geometric quantity, the observations require the modification of present magnetospheric magnetic field models. In particular, the models need to reproduce better the enhanced field observed on the dayside near synchronous orbit.
Pulsed gamma rays from the Crab Pulsar PSR 0531+21 are reported for energies of 0.3 to 30 MeV. The observations were carried out with the UCR gamma ray double Compton scatter telescope launched on a balloon from Palestine, Texas at 4.5 GV, at 2200 LT, September 29, 1978. Two 8 hr observations of the pulsar were made, the first starting at 0700 UT (0200 LT) September 30 just after reaching float altitude of 4.5 g/sq cm. Analysis of the total gamma ray flux from the Crab Nebula plus pulsar using telescope vertical cell pairs was published previously. The results presented supersede the preliminary ones. The double scatter mode of the UCR telescope measures the energy of each incident gamma ray from 1 to 30 MeV and its incident angle to a ring on the sky. The time of arrival is measured to 0.05 ms. The direction of the source is obtained from overlapping rings on the sky. The count rate of the first scatter above a threshold of 0.3 MeV is recorded every 5.12 ms. The Crab Pulsar parameters were determined from six topocentric arrival times of optical pulses.
I present a review of the orbital dynamics of the three body problem of PSR1257+12 and its two putative planetary companions. The orbital dynamics provides two 'reality checks' on the planetary interpretation of the pulse arrival time residuals observed by Wolszczan and Frail (1992). First, by examining the dynamical stability of the system for the deduced orbital periods, one can place upper limits on the companion masses of about two times the mass of Jupiter. Since the lower limits of the companion masses deduced from the observations are well below this upper limit, the planetary interpretation passes this first 'reality check'. Second, the 3:2 near-commensurability of the orbital periods effects periodic variations of the Keplerian orbital parameters. The amplitude of these variations provides a direct measure of the masses of the companions relative to the mass of the pulsar. The signature of these variations in pulse time-of-arrival data is not straightforward, but, if the planetary interpretation is correct, it should become detectable as an additional quasi-periodic phase residual over a period of a few years.
In 2013, the Airspace Operations Laboratory at NASA Ames Research Center conducted a human-in-the-loop simulation that examined the feasibility of applying a number of Next Generation Air Transportation System (NextGen) solutions to complex arrival operations in and around the New York metroplex. The delivery of arrivals to Newark Liberty International Airport (EWR) was the focus of this simulation, which involved extending the Terminal Sequencing and Spacing (TSS) scheduling capability to precisely schedule arrivals to intersecting runways 22 Left and 11. An important enabler for the concept was the availability of a dependent runway scheduler that was able to coordinate arrival times between aircraft landing on intersecting runways. At the time of the study, there was no functionality within the TSS scheduler to automatically create the dependent runway schedules. Instead, a Traffic Management Coordinator (TMC) manually created a de-conflicted schedule, which allowed for the concept to be tested as well as provided valuable insight into the tool requirements for a dependent runway scheduler. Throughout the course of preparations for the simulation, the individual serving as the TMC developed a number of strategies and procedures for manually adjusting the Scheduled Time of Arrival (STA) of the EWR arrivals in order to ensure that adequate spacing was provided between runway 22L and 11 arrival pairs. This paper describes the strategies and procedures that were developed and details how they were successfully applied during the simulation. Results will also be presented that shed additional light on exactly how the schedules were manipulated and their impact on delivery performance and safety. Ideas for additional TSS enhancements and next steps, based on participant feedback, will also be presented.
Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.
The objective of this study is to explore the use of Required Time of Arrival (RTA) capability on the flight deck as a control mechanism on arrival traffic management to improve traffic delivery accuracy by mitigating the effect of traffic demand uncertainty. The uncertainties are caused by various factors, such as departure error due to the difference between scheduled departure and the actual take-off time. A simulation study was conducted using the Multi Aircraft Control System (MACS) software, a comprehensive research platform developed in the Airspace Operations Laboratory (AOL) at NASA Ames Research Center. The Crossing Time (CT) performance (i.e. the difference between target crossing time and actual crossing time) of the RTA for uncertainty mitigation during cruise phase was evaluated under the influence of varying two main factors: wind severity (heavy wind vs. mild wind), and wind error (1 hour, 2 hours, and 5 hours wind forecast errors). To examine the CT performance improvement made by the RTA, the comparison to the CT of the aircraft that were not assigned with RTA (Non-RTA) under the influence of the selected factors was also made. The Newark Liberty International Airport (EWR) was chosen for this study. A total 66 inbound traffic to the EWR (34 of them were airborne when the simulation was initiated, 32 were pre-departures at that time) was simulated, where the pre-scripted departure error was assigned to each pre-departure (61 conform to their Expected Departure Clearance Time, which is +-300 seconds of their scheduled departure time). The results of the study show that the delivery accuracy improvement can be achieved by assigning RTA, regardless of the influence of the selected two factors (the wind severity and the wind information inaccuracy). Across all wind variances, 66.9 (265 out of 396) of the CT performance of the RTA assigned aircraft was within +- 60 seconds (i.e. target tolerance range) and 88.9 (352 out of 396) aircraft met +-300 seconds marginal tolerance range, while only 33.6 (133 out of 396) of the Non-RTA assigned aircrafts CT performance achieved the target tolerance range and 75.5 (299 out of 396) stayed within the marginal. Examination of the impact of different error sources i.e. departure error, wind severity, and wind error suggest that although large departure errors can significantly impact the CT performance, the impacts of wind severity and errors were modest relative the targeted +- 60 second conformance range.
Urban Air Mobility (UAM) is a new transportation concept that enables highly automated, cooperative, passenger or cargo-carrying air transportation services in and around urban areas. To achieve the high level of operational density and complexity desired by the UAM community, an airspace system that allows UAM operators to readily access and operate safely and efficiently in the airspace is needed. This airspace system will require air traffic management designed to reduce the risk of conflicts and loss of separation between UAM flights. In general, strategic conflict management is considered as the first layer of conflict management for safe flight operations to condition the traffic to reduce the need for airborne separation provision, the second layer of conflict management. Demand Capacity Balancing (DCB) is one of the concept components to achieve strategic conflict management. DCB strategically evaluates traffic demand and resource capacities to allow UAM operators to determine when, where and how they operate, while mitigating conflicting needs for airspace and vertiport capacity. DCB can be applied whenever UAM demand exceeds the capacity in airspace or at vertiports. As the UAM ecosystem evolves with advanced technologies and matured operational procedures, more complicated conflict management will likely be needed. In the current UAM ‘Concept of Operation (ConOps) 1.0’ operational stage defined by FAA, however, it will be meaningful to explore the demand capacity balancing at vertiports only, as an initial strategic conflict management approach for UAM operations because vertiport capacity seems to be a bottleneck of UAM traffic. For this research, we developed a demand-capacity imbalance detection and resolution service for UAM. This DCB service identifies the demand from operators and compares the demand to a given capacity at the shared resources (i.e., vertiports) over the upcoming time horizon which is divided into time bins having a constant interval. When a new flight plan is submitted, the algorithm embedded in the DCB service checks the available time bins based on the desired departure time and estimated arrival time at origin and destination vertiports, respectively. If the time bins for the originally desired times are already occupied by other flights (i.e., demand is at or above capacity), the algorithm finds the next available time bins for takeoff and landing and shifts the conflicting departure time to the earliest time that satisfies the capacity constraints at both origin and destination vertiports. The details of the algorithm will be described in the final manuscript. Figure 1 shows that the proposed DCB algorithm works well for a sample traffic scenario. In this example, a total of 144 flights, split between two operators, are planned over 2 hours, traveling 10 routes between five vertiports. In the heatmaps, the horizontal axis shows 12 time bins where each bin represents a 12-minute interval, and the vertical axis shows five vertiports. The number in each cell shows the number of operations, counting both departures and arrivals, at a specific vertiport in each time bin. For the given capacity of 2 operations/vertiport/bin, Figure 1 shows that the original demand sometimes exceeds the capacity, but the modified demand is reduced to the given capacity after resolving demand-capacity imbalances. When UAM flights are operated, it is expected that many practical issues would arise in the federated system architecture with multiple operators. UAM operators may experience a time synchronization issue due to communication delay between operator and vehicle. UAM vehicles would fly at different flight speeds, depending on vehicle models. Actual departure and arrival times can have large variations, compared to the schedule. The lead time from flight plan submission to desired departure time can vary by service type (e.g., regular shuttle service vs. on-demand service). Using the proposed DCB algorithm, we also investigated how the actual flight schedule and DCB performance are affected by these uncertainties such as unsynchronized times between operators, flight speed differences, lead time differences, and departure time errors. The final manuscript will include the background of this research work, the description of the DCB algorithm and its use cases with traffic scenarios. It will also provide the analytical results about the impact of various uncertainties that can occur in actual UAM operations on the DCB at vertiports, in terms of demand distribution changes, number of simultaneous operations, and delay propagation.
The algorithm used in previous technology time-of-arrival lightning mapping systems was based on the assumption that the earth is a perfect spheroid. These systems yield highly-accurate lightning locations, which is their major strength. However, extensive analysis of tower strike data has revealed occasionally significant (one to two kilometer) systematic offset errors which are not explained by the usual error sources. It was determined that these systematic errors reduce dramatically (in some cases) when the oblate shape of the earth is taken into account. The oblate spheroid correction algorithm and a case example is presented.
The problem of retrieving lightning ground strike location on an oblate spheroidal Earth using a network of 4 or more time-of-arrival sensors is considered. A recently developed analytic method for obtaining such retrievals on a spherical Earth surface is perturbed resulting in an iterative procedure to get correction terms. The perturbation procedure consists of applying a vector Newton's method to eqs. relating the distances from the lightning location to each sensor along a geodesic and the times of arrival of the wave produced by the lightning source at each sensor.
In the bus network problem, the goal is to generate a plan for getting from point X to point Y within a city using buses in the smallest expected time. Because bus arrival times are not determined by a fixed schedule but instead may be random. the problem requires more than standard shortest path techniques. In recent work, Datar and Ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed. We offer solutions to two important generalizations of the problem, answering open questions posed by Datar and Ranade. First, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. This class includes not only exponential distributions but also uniform, normal, and gamma distributions. Second, in the case where bus arrival times are independent and geometric discrete random variable,. we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.
We examine the problem of retrieving three-dimensional lightning locations from radio frequency Time-Of-Arrival (TOA) measurements. Arbitrary antenna locations are considered. By judiciously differencing measurements that are related to the location of the antennas and their excitation times, the problem is converted from the initial spherical nonlinear form to a system of linear equations. In the linear formalism, the source location and time-of-occurrence is viewed geometrically as an intersection of hyperplanes in the four-dimensional Minkowski space (x,y,z,t). The linear equations are solved to obtain explicit analytic expressions for the location and time variables. Retrieval errors are not interpreted with conventional Geometrical Dilution of Precision (GDOP) arguments as discussed by Holmes and Reedy (1951), but with more recent inversion analyses considered by Twomey (1977). Measurement errors are propagated analytically so that the specific effect of these errors on the solution is clarified. The sensitivity of the solution on the number of antennas used, antenna network geometry, source position, and measurement differencing schemes are discussed in terms of the eigenvalues of the linear system.
A common problem in optical detection is determining the arrival time of a weak optical pulse that may comprise only one to a few photons. Currently, this problem is solved by using a photodetector to convert the optical signal to an electronic signal. The timing of the electrical signal is used to infer the timing of the optical pulse, but error is introduced by random delay between the absorption of the optical pulse and the creation of the electrical one. To eliminate this error, a time-to-space converter separates a sequence of optical pulses and sends them to different photodetectors, depending on their arrival time. The random delay, called jitter, is at least 20 picoseconds for the best detectors capable of detecting the weakest optical pulses, a single photon, and can be as great as 500 picoseconds. This limits the resolution with which the timing of the optical pulse can be measured. The time-to-space converter overcomes this limitation. Generally, the time-to-space converter imparts a time-dependent momentum shift to the incoming optical pulses, followed by an optical system that separates photons of different momenta. As an example, an electro-optic phase modulator can be used to apply longitudinal momentum changes (frequency changes) that vary in time, followed by an optical spectrometer (such as a diffraction grating), which separates photons with different momenta into different paths and directs them to impinge upon an array of photodetectors. The pulse arrival time is then inferred by measuring which photodetector receives the pulse. The use of a time-to-space converter mitigates detector jitter and improves the resolution with which the timing of an optical pulse is determined. Also, the application of the converter enables the demodulation of a pulse position modulated signal (PPM) at higher bandwidths than using previous photodetector technology. This allows the creation of a receiver for a communication system with high bandwidth and high bits/photon efficiency.
The first RF pulse from "total lightning' discharges (cloud and ground flashes) has been used in different ways to locate the origin of flashes in two new types of lightning detection systems. The multisensor LASI time-of-arrival (TOA) system uses GPS timing of the first pulse. The ATLAS single sensor system uses the amplitude of the first pulse, which is invariant in magnitude and polarization for all lightning discharges, to determine distance from the sensor. It is significantly more accurate than past single sensor lightning mapping systems. The polarity of the first pulse generally identifies lightning type (IC or CG). Both systems utilize only the first pulse which makes signal processing much simpler than with previous lightning locating systems. Knowing the position where lightning begins (maximum electric fields, mixed phase hydrometeors and updrafts) is valuable for identifying convective cells producing the hazardous meteorological conditions caused by thunderstorms. It is also important for research studying thunderstorm electrification and associated microphysical problems.