UAT ADS-B Data Anomalies and the Effect of Flight Parameters on Dropout Occurrences

An analysis of the performance of automatic dependent surveillance-broadcast (ADS-B) data received from the Grand Forks, North Dakota International Airport was carried out in this study. The purpose was to understand the vulnerabilities of the universal access transceiver (UAT) ADS-B system and recognize the effects on present and future air traffic control (ATC) operation. The Federal Aviation Administration (FAA) mandated all the general aviation aircraft to be equipped with ADS-B. The aircraft flying within United States and below the transition altitude (18,000 feet) are more likely to install a UAT ADS-B. At present, unmanned aircraft systems (UAS) and autonomous air traffic control (ATC) towers are being integrated into the aviation industry and UAT ADS-B is a basic sensor for both class 1 and class 2 detect-and-avoid (DAA) systems. As a fundamental component of future surveillance systems, the anomalies and vulnerabilities of the ADS-B system need to be identified to enable a fully-utilized airspace with enhanced situational awareness. The data received was archived in GDL-90 format, which was parsed into readable data. The anomaly detection of ADS-B messages was based on the FAA ADS-B performance assessment report. The data investigation revealed ADS-B message suffered from different anomalies including dropout, missing payload, data jump, low confidence data, and altitude discrepancy. Among those studied, the most severe was dropout and 32.49% of messages suffered from this anomaly. Dropout is an incident where ADS-B failed to update within a specified rate. Considering the potential danger being imposed, an in-depth analysis was carried out to characterize message dropout. Three flight parameters were selected to investigate their effect on dropout. Statistical analysis was carried out and the Friedman Statistical Test identified that altitude affected dropout more than any other flight parameter

UAS Surveillance Criticality

The integration of unmanned aircraft systems (UAS) into the national airspace system (NAS) poses considerable challenges. Maintaining human safety is perhaps chief among these challenges as UAS remote pilots will need to interact with other UAS, piloted aircraft, and other conditions associated with flight. A research team of 6 leading UAS research universities was formed to respond to a set of surveillance criticality research questions. Five analysis tools were selected following a literature review to evaluate airborne surveillance technology performance. The analysis tools included: Fault Trees, Monte Carlo Simulations, Hazard Analysis, Design of Experiments (DOE), and Human-in-the-Loop Simulations. The Surveillance Criticality research team used results from these analyses to address three primary research questions and provide recommendations for UAS detect-and-avoid mitigation and areas for further research

UTILIZING UAV PAYLOAD DESIGN BY UNDERGRADUATE RESEARCHERS FOR EDUCATIONAL AND RESEARCH DEVELOPMENT

ABSTRACT An undergraduate team consisting of mechanical and electrical engineering students at the University of North Dakota developed an electro-optical and un-cooled thermal infrared digital imaging remote sensing payload for an Unmanned Aerial Vehicle (UAV). The first iteration of the payload design began in the fall of 2005 and the inaugural flight tests took place at Camp Ripley, Minnesota, a National Guard facility, in the fall of 2006 with a corporate partner. The second iteration design with increased performance in object tracking and data processing is expected to fly in the summer of 2007. Payload development for integration into a UAV is a process that is not currently well defined by industrial practices or regulated by government. These processes are a significant part of the research being conducted in order to define the "best practices." The emerging field of UAVs generates tremendous interest and serves to attract quality students into the research. As with many emerging technologies there are many new exciting developments, however, the fundamentals taught in core courses are still critical to the process and serve as the basis of the system. In this manner, the program stimulates innovative design while maintaining a solid connection to undergraduate courses and illustrates the importance of advanced courses. The payload development was guided by off-the-shelf components and software using a systems engineering methodology throughout the project. Many of the design and payload flight constraints were based on external factors, such as difficulties with access to airspace, weatherrelated delays, and ITAR restrictions on hardware. Overall, the research project continues to be a tremendous experiential learning activity for mechanical and electrical engineering students, as well as for the faculty members. The process has been extremely successful in enhancing the expertise in systems engineering and design in the students and developing the UAV payload design knowledge base and necessary infrastructure at the university

Small UAS Detect and Avoid Requirements Necessary for Limited Beyond Visual Line of Sight (BVLOS) Operations

Potential small Unmanned Aircraft Systems (sUAS) beyond visual line of sight (BVLOS) operational scenarios/use cases and Detect And Avoid (DAA) approaches were collected through a number of industry wide data calls. Every 333 Exemption holder was solicited for this same information. Summary information from more than 5,000 exemption holders is documented, and the information received had varied level of detail but has given relevant experiential information to generalize use cases. A plan was developed and testing completed to assess Radio Line Of Sight (RLOS), a potential key limiting factors for safe BVLOS ops. Details of the equipment used, flight test area, test payload, and fixtures for testing at different altitudes is presented and the resulting comparison of a simplified mathematical model, an online modeling tool, and flight data are provided. An Operational Framework that defines the environment, conditions, constraints, and limitations under which the recommended requirements will enable sUAS operations BVLOS is presented. The framework includes strategies that can build upon Federal Aviation Administration (FAA) and industry actions that should result in an increase in BVLOS flights in the near term. Evaluating approaches to sUAS DAA was accomplished through five subtasks: literature review of pilot and ground observer see and avoid performance, survey of DAA criteria and recommended baseline performance, survey of existing/developing DAA technologies and performance, assessment of risks of selected DAA approaches, and flight testing. Pilot and ground observer see and avoid performance were evaluated through a literature review. Development of DAA criteria—the emphasis here being well clear— was accomplished through working with the Science And Research Panel (SARP) and through simulations of manned and unmanned aircraft interactions. Information regarding sUAS DAA approaches was collected through a literature review, requests for information, and direct interactions. These were analyzed through delineation of system type and definition of metrics and metric values. Risks associated with sUAS DAA systems were assessed by focusing on the Safety Risk Management (SRM) pillar of the SMS (Safety Management System) process. This effort (1) identified hazards related to the operation of sUAS in BVLOS, (2) offered a preliminary risk assessment considering existing controls, and (3) recommended additional controls and mitigations to further reduce risk to the lowest practical level. Finally, flight tests were conducted to collect preliminary data regarding well clear and DAA system hazards

UAT ADS-B Data Anomalies and the Effect of Flight Parameters on Dropout Occurrences

An analysis of the performance of automatic dependent surveillance-broadcast (ADS-B) data received from the Grand Forks, North Dakota International Airport was carried out in this study. The purpose was to understand the vulnerabilities of the universal access transceiver (UAT) ADS-B system and recognize the effects on present and future air traffic control (ATC) operation. The Federal Aviation Administration (FAA) mandated all the general aviation aircraft to be equipped with ADS-B. The aircraft flying within United States and below the transition altitude (18,000 feet) are more likely to install a UAT ADS-B. At present, unmanned aircraft systems (UAS) and autonomous air traffic control (ATC) towers are being integrated into the aviation industry and UAT ADS-B is a basic sensor for both class 1 and class 2 detect-and-avoid (DAA) systems. As a fundamental component of future surveillance systems, the anomalies and vulnerabilities of the ADS-B system need to be identified to enable a fully-utilized airspace with enhanced situational awareness. The data received was archived in GDL-90 format, which was parsed into readable data. The anomaly detection of ADS-B messages was based on the FAA ADS-B performance assessment report. The data investigation revealed ADS-B message suffered from different anomalies including dropout, missing payload, data jump, low confidence data, and altitude discrepancy. Among those studied, the most severe was dropout and 32.49% of messages suffered from this anomaly. Dropout is an incident where ADS-B failed to update within a specified rate. Considering the potential danger being imposed, an in-depth analysis was carried out to characterize message dropout. Three flight parameters were selected to investigate their effect on dropout. Statistical analysis was carried out and the Friedman Statistical Test identified that altitude affected dropout more than any other flight parameter

Assessing the Effect of ADS-B Message Drop-Out in Detect and Avoid of Unmanned Aircraft System Using Monte Carlo Simulation

This work analyzes the severity and risk associated with automatic dependent surveillance-broadcast (ADS-B) message drop-out in detect and avoid (DAA) function of unmanned aircraft systems (UAS). Performance assessment of the universal access transceiver (UAT) ADS-B message implies that, in some cases, ADS-B fails to update within a specified update interval, which is referred to as ‘drop-out’ in this work. ADS-B is a fundamental surveillance sensor for both class 1 and class 2 DAA systems. Message loss or drop-out has been found as one of the common limitations of the ADS-B system. The key feature of this study is incorporating the update rate of real ADS-B data transmitted from the manned aircraft. The data were received from the Grand Forks International Airport, North Dakota. Monte Carlo method has been adopted to resolve encounter scenarios in the presence of drop-out. The change in the alert triggered by the UAS DAA in the presence of ADS-B drop-out has been investigated. Furthermore, the risk matrices are created to quantify the associated risk with drop-out affected alerts. Simulation results depict that both the duration of drop-out and DAA look-ahead time affect the alert-triggering function of UAS. With a small look-ahead window and longer duration of drop-out, the number of warning alerts increases. Also, alerts are affected more during an overtaking encounter than that of a head-to-head encounter. A system-level analysis is also carried out to recognize the potential reasons behind the ADS-B drop-out

The Reduction of Modal Sensor Channels through a Pareto Chart Methodology

Presented herein is a new experimental sensor placement procedure developed to assist in placing sensors in key locations in an efficient method to reduce the number of channels for a full modal analysis. It is a fast, noncontact method that uses a laser vibrometer to gather a candidate set of sensor locations. These locations are then evaluated using a Pareto chart to obtain a reduced set of sensor locations that still captures the motion of the structure. The Pareto chart is employed to identify the points on a structure that have the largest reaction to an input excitation and thus reduce the number of channels while capturing the most significant data. This method enhances the correct and efficient placement of sensors which is crucial in modal testing. Previously this required the development and/or use of a complicated model or set of equations. This new technique is applied in a case study on a small unmanned aerial system. The test procedure is presented and the results are discussed

The evolving role of the state hospital in the care and treatment of older adults: state trend, 1984 to 1993

OBJECTIVE: To understand the current and potential role of state hospitals in serving geriatric patients, national trends in the use of state mental hospitals by adults age 65 and older were examined. METHODS: State hospital use by older adults in the 50 states and the District of Columbia was compared for the years 1984 and 1993 using published data from the Center for Mental Health Services. RESULTS: Nationally, the number of state hospital admissions and residents declined between 1984 and 1993, and the rate of decrease was greater for older adults than for younger adults. However, states varied considerably in the rate of decrease in the number of older adult state hospital residents and admissions and in the proportion of older adult patients diagnosed with an organic mental disorder. In ten states, the older-adult state hospital population increased. CONCLUSIONS: Although the national trend is toward a declining role for state hospitals in treatment and care of older adults, in several states the hospitals fill an important function in providing custodial care and acute care for this population