2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)最新文献

{"title":"Optimal Aircraft Rerouting during Space Launches using Adaptive Spatial Discretization","authors":"Rachael E. Tompa, Mykel J. Kochenderfer","doi":"10.1109/DASC.2018.8569888","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569888","url":null,"abstract":"To ensure safety during space launches, the Federal Aviation Administration restricts a column of airspace around the launch location and anticipated trajectory. These restrictions are often in place for hours at a time and lead to many rerouted aircraft. Recent research has focused on making these restrictions dynamic and constraining their volume. Previously, the problem was framed as a Markov decision process and solved using dynamic programming. A major challenge with this prior formulation is its computational tractability, and its application required a relatively course spatial discretization. This paper presents an, adaptive spatial discretization method, that provides a finer discretization in the spatial regions where an aircraft may need to start rerouting. This scalable method results in less disruption in the airspace while reducing risk.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128591845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aircraft Proximity: a synthesis of Apollonius, X-track, and Well Clear Volume paradigms","authors":"N. Fulton, Grace S. Garden, Sarah A. Mecklem, Brendan Williams, R. Clothier","doi":"10.1109/DASC.2018.8569870","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569870","url":null,"abstract":"The introduction of Unmanned Aircraft Systems (UAS) operating aerial vehicles in non-segregated airspace has sparked renewed interest into the problem of how to specify a Well-Clear Volume (WCV) for aircraft proximity. A pertinent example is the Self-Separation Volume (SSV) being developed by NASA for use in UAS Detect and Avoid (DAA) systems. To date, the generation and validation of candidate WCVs has been reliant on exhaustive simulation. Complementary research has been directed at the formalization of the Apollonius Circle paradigm in characterizing proximity for two aircraft. Recent research by Westcott, Fulton and Smith has cast the crossing-track problem in a Compromise Decision Support paradigm. In this paper the three approaches are synthesized into a single cohesive geometric model that is then used as an engineering validation tool to test the NASA SSV paradigm (a specific instance of a Well-Clear Volume). The geometric model for proximate operations is based on a Feasible Design Space that partitions into well identified geometric regions delineated by the Line of Sight (LOS) Circle and the Apollonius Circle. The LOS Circle provides insight as to the Geometric Dilution of Precision required in error analysis and also facilitates determination of the behavior of the distance at closest approach vector. The Apollonius Circle identifies, for a constant speed ratio, the locus of all possible collision points within the 2D conflict plane. The model developed in this paper facilitates a more robust geometric construction of the SSV with transparent testing and satisfaction of the operational requirements thus providing a consolidated benchmark reference for further engineering construction of WCVs.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116313729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of the human operator in future commercial Reduced Crew Operations","authors":"Sebastian M. Sprengart, Stefan Manuel Neis, J. Schiefele","doi":"10.1109/DASC.2018.8569803","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569803","url":null,"abstract":"Reduced Crew Operations (RCO) are a longstanding concept in academia and slowly reaching into the realm of actual airline operations. However, one of the great barriers is the role definition of the future single pilot. Simply removing one of the pilots will not work - a more comprehensive approach is required. As re-certification of the flight deck will be required anyway, we are offered to unique chance to rethink flight deck operations and properly (re-)consider the role a human operator on the flight deck will perform. Lead by the question if today's pilots are still acting as pilots we present a new role definition for the future RCO flight deck operator. As an introduction, the development of the flight deck and the associated role change of the human operator from being an aviator to a manager of systems is highlighted. Subsequently an overview over existing future flight deck concepts is given, focusing on RCO oriented approaches. The development process through which the herein presented concept was created is stated in the following. First, the underlying technological, operational, and legal assumptions and limitations are summarized. After that the goals to which the concept is supposed to cater are introduced, followed by a description of the utilized development process. Hereafter, the role definition of the human operator is discussed. We envision the human operator to take over a more strategic role than today. Instead of managing individual aircraft systems the operator will be tasked with Total Mission Management (TMM), supported by advanced, more autonomous, automation. Hence, we propose to change the job title of the human operator from pilot to mission manager. A set of typical tasks of the mission manager is described positively (what they are) and negatively (what they are not). Furthermore, the question of responsibility and authority on the flight deck is answered. Eventually, existing challenges and future research efforts regarding the herein proposed concept are discussed.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"55 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116384694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of Numerical Methods for Aircraft Trajectory Computation","authors":"S. Torres","doi":"10.1109/DASC.2018.8569850","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569850","url":null,"abstract":"Aircraft trajectories are used by ground automation systems that support Air Traffic Management (ATM) operations. The performance of these operations depends on the accuracy of the trajectories. This paper presents an analysis of numerical methods used by trajectory predictors to solve the equations of motion. The accuracy of numerical methods for Ordinary Differential Equations (ODEs) depend on the order of the approximations when evaluating the derivatives to be integrated. There is a tradeoff between accuracy and computational efficiency. It is found that standard methods, such as 2nd order Runge-Kutta, are adequate for nominal conditions. However, discontinuities in some of the terms in the equations for vertical rate and the presence of vertical wind gradients may benefit from more sophisticated methods. A new method, the Adaptive Altitude (AdAL) step method, that changes the independent variable from time to altitude is proposed and evaluated. The AdAL method yields a performance comparable to 2nd order, but at half the computational load. Results are presented for climb and descent scenarios under different wind conditions. Accuracy and numerical stability metrics are presented. Operational impact of errors is discussed.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117066626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Clear Air Turbulence by Airborne Weather Radar using RR-MWF Method","authors":"R. Wu, Yuandan Fan, Xiaoguang Lu, Zhe Zhang, Hai Li","doi":"10.1109/DASC.2018.8569571","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569571","url":null,"abstract":"The precipitation of CAT (Clear Air Turbulence) is lower than that of the convective turbulence, resulting low SNR echoes are received by airborne weather radars in the detection of CAT. This will inevitably lead to poor performance on spectrum width estimation where pulse pair processing (PPP) method is used. To address this issue, an echo spectral moments estimation method based on reduced-rank multistage wiener filter (RR-MWF) is proposed by introducing space-time adaptive processing algorithm for airborne weather radar turbulence detection performance enhancement in low SNR scenarios. The proposed method inherits the capability of enhancing echo SNR by accumulating signals coherently, both in the spatial and the temporal dimensions. The adaptive RR-MWF weighted vector and cost function are constructed under the MSE (Mean Square Error) criterion, therefore the spectral moments can be accurately estimated for CAT, which is considered as one of the distributed weather targets. Numerical simulations show that the RR-MWF outmatches the PPP method when SNR is lower than 10dB, therefore demonstrating its effectiveness in low SNR scenarios.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117172658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-Flight Performance Analysis of a Wideband Radio Using SDR for Avionic Applications","authors":"A. Nguyen, A. Amrhar, Eric Zhang, J. Zambrano, R. Landry","doi":"10.1109/DASC.2018.8569880","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569880","url":null,"abstract":"Along with the increase in the number of passengers, aviation industry also needs to be adapted to the increasing demands of new services and applications. As one of the leading features of the Industry 4.0 era, maintaining a constant and high quality internet connectivity in-flight (also known as the In-Flight Entertainment Connectivity, IFEC) is one of the most demanded services. Among the explored solutions, the Wideband Radio (WBR), first presented in 2017 as a module in the Multi-Mode Software Defined Avionic Radio (MM-SDAR), is the avionic module that addresses the ever-increasing demand for the IFEC application. Based on the Adaptive Coding and Modulation (ACM) scheme, this Software Defined Avionic Module (SDAM) promises to deliver an optimum data rate regarding the real-time condition of the transmission channels. Moreover, as an SDR-based module, it is reconfigurable and could be implemented in an IMA-compatible (Integrated Modular Avionics) fashion in the future RF avionic architecture. In order to evaluate the operation of this WBR module in real flight conditions, it was flight tested in 2017, and positive results were obtained. This paper aims to provide an analysis of the in-flight performance (with Bit Error Rate - BER mode and video streaming mode) of the WBR, and concentrates on demonstrating the capacity and the operation of the ACM mechanism in a complex environment. With a transmission power of 10 W and a bandwidth of 675 kHz, the maximum slant range of the WBR during these flights reached 5 NM, and the ACM mechanism helped the system maintain an average throughput of around 360 kbit/s.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115396568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In- Time Safety Assurance Systems for Emerging Autonomous Flight Operations","authors":"S. Young, Cuong Quach, K. Goebel, J. Nowinski","doi":"10.1109/DASC.2018.8569689","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569689","url":null,"abstract":"As aviation adopts new operational paradigms, new vehicle types, and new technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before they become hazards. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments wherein the interplay of hazards may not be known, and cannot be accounted for at design time. They also can help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected nondeterministic behaviors. The envisioned monitoring functions can observe these behaviors and apply model-based and data-driven methods to drive downstream assessment and mitigation functions, thereby providing a level of run-time assurance. This paper presents a preliminary conceptual design of such an in-time safety assurance system for highly-autonomous aircraft operating at low altitudes near and over populated areas. Research, development, and evaluation tests are initially aimed at public-use surveillance missions such as those needed for infrastructure inspection, facility management, emergency response, law enforcement, and/or security. A longer term goal is to support transportation missions such as medical specimen delivery and urban air mobility. Safety-critical risks initially addressed within the system concept were identified in previous work by NASA and others in industry. These include: flight outside of approved airspace; unsafe proximity to people or property; critical system failures including loss of link, loss or degraded positioning system performance, loss of power, and engine failure; loss-of-control due to envelope excursion or flight control system failure; and cyber-security related risks.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127568345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Viability of the Use of Aircraft-generated Intent Data for Air Traffic Management","authors":"G. Saccone, R. Mead","doi":"10.1109/DASC.2018.8569363","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569363","url":null,"abstract":"As air navigation service providers (ANSPs) move towards trajectory-based operations (TBO), the use of aircraft-provided information is increasingly viewed as a relied-upon capability. The expected benefits from the use of extended projected profile (EPP) information in Europe has been cited as a major driver for aircraft and ground equipage. However, early trials using EPP intent information, while showing some promise, also highlighted areas where usage may be more problematic (e.g. shifting estimated times of arrival windows, Top of Climb/Descent, etc). This also coincides with studies on aircraft intent data performed at Boeing using data from both revenue flights and high-fidelity aircraft simulators. Providing information on the data types, their use in the aircraft, and therefore the data generation algorithms will assist ground system providers in integrating such data into their tools and capabilities. While aircraft intent information such as EPP and other data directly from avionics are definitely useful in enhancing ground trajectory calculations and predictions, there are a number of critical areas that must be further understood in order take full advantage of this data. This includes, at a basic level, an understanding of how the aircraft is being flown, how the avionics manages control of the aircraft, the purpose of the intent data produced on the aircraft (which is different from the purpose of use on the ground), what the aircraft and avionics are doing (or have recently done) at the time that the reported data is obtained prior to downlinking, and how all of those conditions relate to the data provided. These all have an impact on the quality and accuracy of the aircraft-provided data, and a ground system using this data must take these factors into account on an individual aircraft basis in order to arrive at a useful interpretation of the data. This paper will detail different types of information from aircraft that are both currently available and expected to be available in the near-to-mid-term. It will also discuss how flight management computers (FMCs) calculate and use information to control the aircraft, and how that data and its usage differs from how ground systems generally interpret that data. There will also be considerations given on how aircraft-provided data is used by ground systems, and for what purposes (e.g. can the data be used for separation). Finally, analysis and results citing real-world and aircraft simulator data from work done both internally at Boeing as well as from referenced external sources will be given. These will identify various situations that illustrate how interpretations of aircraft data may be misconstrued without some knowledge of the conditions under which the data was generated. The conclusions","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126929417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-training by Reinforcement Learning for Full-autonomous Drones of the Future*","authors":"Kjell Kersandt, G. Muñoz, C. Barrado","doi":"10.1109/DASC.2018.8569503","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569503","url":null,"abstract":"Drones are rapidly increasing their activity in the airspace worldwide. This expected growth of the number of drones makes human-based traffic management prohibitive. Avionics systems able to sense-and-avoid obstacles and specially visual flight rules (VFR) traffic are under research. Moreover, to overcome loss-link contingencies, drones have to be able to act autonomously. In this paper we present a drone concept with a full level of autonomy based on Deep Reinforcement Learning (DRL). From the first flight until the accomplishment of its final mission, the drone has no need for a pilot. The only human intervention is the engineer programming the artificial intelligence algorithm used to train and then to control the drone. In this paper we present the preliminary results for an environment which is a realistic flight simulator, and an agent that is a quad-copter drone able to execute 3 actions. The inputs of the agent are the current state and the accumulated reward. Experiments include self-learning periods up to 3 days, followed by one hundred full-autonomous flight tests. Three different DRL algorithms were used to obtain the training models, based in Q-learning reinforcement learning. Results are very promising, with around an 80 percent of test flights reaching the target. In comparison with the results of a human pilot, acting in the same simulated environment and using the same three actions, the DRL methods demonstrated unequal results, depending on the learning algorithm used. We applied some enhancements in the training, with the creation of checkpoints of the training model every time a better solution is found. In a near future we expect to achieve results similar to the performance of a human pilot to support the idea of full-autonomous drones through DRL methods.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125893652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Implementation Analysis of Communications, Navigation, and Surveillance (CNS) Technologies for Unmanned Air Systems (UAS)","authors":"D. Ponchak, F. Templin, Greg Sheffield, Pedro Taboso, R. Jain","doi":"10.1109/DASC.2018.8569660","DOIUrl":"https://doi.org/10.1109/DASC.2018.8569660","url":null,"abstract":"The aviation industry and government agencies face a rapidly-emerging need for integrating large-scale populations of Unmanned Air Systems (UAS) into the worldwide controlled and uncontrolled airspace. Critical components for integration include the Communications, Navigation, and Surveillance (CNS) technologies necessary for ensuring safe UAS operations. Under NASA program NNA16BD84C, our work on CNS architectural concepts for the safe operation of UAS in controlled and uncontrolled airspace has introduced CNS architectures which must be analyzed in terms of implementation readiness. Controlled airspace operations for UAS are consistent with the needs for manned aviation in the worldwide Air Traffic Management (ATM) service. Uncontrolled airspace operations are consistent with the NASA Unmanned (air) Traffic Management (UTM) concept of operations. Implementation readiness is based on the NASA concept of Technology Readiness Levels (TRLs) ranging from TRL1 (basic principles observed and reported) to TRL9 (actual system flight proven through successful mission operations). In the architecture concepts, we have introduced a number of new CNS architectural elements which need to be correlated with TRL levels. In this paper, we present our implementation analysis for communications networks, communications data links, navigation, and surveillance. Each area has been under active research and development during the course of the current NASA program which has produced studies on UAS CNS Requirements, UAS CNS Architecture for Controlled Airspace and UAS CNS Architecture for Uncontrolled Airspace. We have published our architecture concepts in major UAS-related conferences (including iCNS2017, IEEE Aerospace 2018, and iCNS2018) and will continue to seek additional publication opportunities. We look forward to continuing our work to realize a full integration testing scenario for both controlled and uncontrolled airspace operation.","PeriodicalId":405724,"journal":{"name":"2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124314255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}