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Evaluating collision avoidance for small UAS using ACAS X

Author:
Published in:
AIAA SciTech Forum, 6-10 January 2020.

Summary

Small Unmanned Aircraft Systems (sUAS) offer many potential benefits to society but also pose a dangerous mid-air collision hazard. Safely integrating into shared airspace will require sUAS to perform Collision Avoidance (CA), one of the primary components of Detect and Avoid (DAA) technologies. This paper performs a Monte Carlo simulation of close encounters between sUAS and manned aircraft to evaluate the safety and alerting rates of three CA system architecture options: manned aircraft avoiding sUAS, sUAS avoiding manned aircraft, and both types of aircraft avoiding each other. Novel CA policies based on ACAS X are introduced for sUAS. These policies enable sUAS to perform escape maneuvers with far lower vertical climb capabilities than what is expected by current CA systems.
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Summary

Small Unmanned Aircraft Systems (sUAS) offer many potential benefits to society but also pose a dangerous mid-air collision hazard. Safely integrating into shared airspace will require sUAS to perform Collision Avoidance (CA), one of the primary components of Detect and Avoid (DAA) technologies. This paper performs a Monte Carlo simulation...

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Representative small UAS trajectories for encounter modeling

Published in:
AIAA SciTech Forum, 6-10 January 2020.

Summary

As unmanned aircraft systems (UASs) continue to integrate into the U.S. National Airspace System (NAS), there is a need to quantify the risk of airborne collisions between unmanned and manned aircraft to support regulation and standards development. Both regulators and standards developing organizations have made extensive use of Monte Carlo collision risk analysis simulations using probabilistic models of aircraft flight. We have previously demonstrated a methodology for developing small unmanned aircraft system (sUAS) flight models that leverage open source geospatial information and map datasets to generate representative unmanned operations at low altitudes. This work expands upon previous research by evaluating the scalability and diversity of open source data to support currently needed risk assessments. We also provide considerations for pairing these trajectories with generative manned aircraft models to create encounters for Monte Carlo simulations.
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Summary

As unmanned aircraft systems (UASs) continue to integrate into the U.S. National Airspace System (NAS), there is a need to quantify the risk of airborne collisions between unmanned and manned aircraft to support regulation and standards development. Both regulators and standards developing organizations have made extensive use of Monte Carlo...

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Command and control for multifunction phased array radar

Published in:
IEEE Trans. Geosci. Remote Sens., Vol. 55, No. 10, October 2017, pp. 5899-5912.

Summary

We discuss the challenge of managing the Multifunction Phased Array Radar (MPAR) timeline to satisfy the requirements of its multiple missions, with a particular focus on weather surveillance. This command and control (C2) function partitions the available scan time among these missions, exploits opportunities to service multiple missions simultaneously, and utilizes techniques for increasing scan rate where feasible. After reviewing the candidate MPAR architectures and relevant previous research, we describe a specific C2 framework that is consistent with a demonstrated active array architecture using overlapped subarrays to realize multiple, concurrent receive beams. Analysis of recently articulated requirements for near-airport and national-scale aircraft surveillance indicates that with this architecture, 40–60% of the MPAR scan timeline would be available for the high-fidelity weather observations currently provided by the Weather Service Radar (WSR-88D) network. We show that an appropriate use of subarray generated concurrent receive beams, in concert with previously documented, complementary techniques to increase the weather scan rate, could enable MPAR to perform full weather volume scans at a rate of 1 per minute. Published observing system simulation experiments, human-in-the-loop studies and radar-data assimilation experiments indicate that high-quality weather radar observations at this rate may significantly improve the lead time and reliability of severe weather warnings relative to current observation capabilities.
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Summary

We discuss the challenge of managing the Multifunction Phased Array Radar (MPAR) timeline to satisfy the requirements of its multiple missions, with a particular focus on weather surveillance. This command and control (C2) function partitions the available scan time among these missions, exploits opportunities to service multiple missions simultaneously, and...

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En route sector capacity model final report

Author:
Published in:
MIT Lincoln Laboratory Report ATC-426

Summary

Accurate predictions of en route sector capacity are vital when analyzing the benefits of proposed new air traffic management decision-support tools or new airspace designs. Controller workload is the main determinant of sector capacity. This report describes a new workload-based capacity model that improves upon the Federal Aviation Administration's current Monitor Alert capacity model. Analysts often use Monitor Alert sector capacities in evaluating the benefits of decision-support aids or airspace designs. However, Monitor Alert, which was designed to warn controllers of possible sector overload, sets sector capacity limits based solely on handoff workload and fixed procedural constraints. It ignores the effects of conflict workload and recurring workload (from activities such as monitoring, vectoring, spacing, and metering). Each workload type varies differently as traffic counts and airspace designs are changed. When used for benefits analysis, Monitor Alert's concentration on a single workload type can lead to erroneous conclusions. The new model considers all three workload types. We determine the relative contribution of the three workload types by fitting the model to the upper frontiers that appear in peak daily sector traffic counts from today's system. When we fit the Monitor Alert model to these same peak traffic counts, it can only explain the observed frontiers by hypothesizing large handoff workload. Large handoff workload would imply that decision-support aids should focus on handoff tasks. The new model fits the traffic data with less error, and shows that recurring tasks create significantly more workload in all sectors than do handoff tasks. The new model also shows that conflict workload dominates in very small sectors. These findings suggest that it is more beneficial to develop decision-support aids for recurring tasks and conflict tasks than for handoff tasks.
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Summary

Accurate predictions of en route sector capacity are vital when analyzing the benefits of proposed new air traffic management decision-support tools or new airspace designs. Controller workload is the main determinant of sector capacity. This report describes a new workload-based capacity model that improves upon the Federal Aviation Administration's current...

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ASR-9 Weather Systems Processor technology refresh and upgrade

Summary

The Weather Systems Processor (WSP) is an add-on system to the Airport Surveillance Radar-9 (ASR-9) that generates wind shear detection and storm tracking products for the terminal airspace. As the original system ages and pre-purchased replacement parts in the depot are used up, it becomes increasingly problematic to procure hardware components for repairs. Thus, a technical refresh is needed to sustain WSP operations into the future. This phase of the project targets the intermediate frequency digital receiver, the radar interface module, and the digital signal processor for replacement by updated hardware platforms. At the same time, the increase in computational capability allows for an upgrade in the signal processing algorithm, which will lead to data quality improvements.
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Summary

The Weather Systems Processor (WSP) is an add-on system to the Airport Surveillance Radar-9 (ASR-9) that generates wind shear detection and storm tracking products for the terminal airspace. As the original system ages and pre-purchased replacement parts in the depot are used up, it becomes increasingly problematic to procure hardware...

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Advisory services for user composition tools

Summary

We have developed an ontology based framework that evaluates compatibility between processing modules within an end user development framework, using MIT Lincoln Laboratory's Composable Analytics environment as a test case. In particular, we focus on inter-module semantic compatibility as well as compatibility between data and modules. Our framework includes a core ontology that provides an extendible vocabulary that can describe module attributes, module input and output requirements and preferences, and data characteristics that are pertinent to selecting appropriate modules in a given situation. Based on the ontological description of the modules and data, we first present a framework that takes a rule based approach in measuring semantic compatibility. Later, we extend the rule based approach to a flexible fuzzy logic based semantic compatibility evaluator. We have built an initial simulator to test module compatibility under varying situations. The simulator takes in the ontological description of the modules and data and calculates semantic compatibility. We believe the framework and simulation environment together will help both the developers test new modules they create as well as support end users in composing new capabilities. In this paper, we describe the details of the framework, the simulation environment, and our iterative process in developing the module ontology.
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Summary

We have developed an ontology based framework that evaluates compatibility between processing modules within an end user development framework, using MIT Lincoln Laboratory's Composable Analytics environment as a test case. In particular, we focus on inter-module semantic compatibility as well as compatibility between data and modules. Our framework includes a...

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Unmanned aircraft sense and avoid radar: surrogate flight testing performance evaluation

Summary

Unmanned aircraft systems (UAS) have proven to have distinct advantages compared to manned aircraft for a variety of tasks. Current airspace regulations require a capability to sense and avoid other aircraft to replace the ability of a pilot to see and avoid other traffic. A prototype phased-array radar was developed and tested to demonstrate a capability to support the sense and avoid (SAA) requirement and to validate radar performance models. Validated radar models enable evaluation of other radar systems in simulation. This paper provides an overview of the unique radar technology, and focuses on radar performance and model validation as demonstrated through a flight testing campaign. Performance results demonstrate that the prototype SAA radar system can provide sufficient accuracy to sense avoid non-cooperative aircraft.
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Summary

Unmanned aircraft systems (UAS) have proven to have distinct advantages compared to manned aircraft for a variety of tasks. Current airspace regulations require a capability to sense and avoid other aircraft to replace the ability of a pilot to see and avoid other traffic. A prototype phased-array radar was developed...

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Secondary Surveillance Phased Array Radar (SSPAR): initial feasibility study

Summary

The U.S. Federal Aviation Administration is deploying Automatic Dependent Surveillance-Broadcast (ADS-B) to provide next-generation surveillance derived through down- and cross-link of global positioning satellite (GPS) navigation data. While ADS-B will be the primary future surveillance system, FAA recognizes that backup surveillance capabilities must be provided to assure that air traffic control (ATC) services can continue to be provided when individual aircraft transponders fail and during localized, short-duration GPS outages. This report describes a potential ADS-B backup capability, Secondary Surveillance Phased Array Radar or SSPAR. SSPAR will interrogate aircraft transponders and receive replies using a sparse, non-rotating array of approximately 17 omnidirectional (in azimuth) antennae. Each array element will transmit and receive independently so as to form directional transmit beams for transponder interrogation, and support high-resolution direction finding for received signals. Because each SSPAR element is independently digitized, transponder returns from all azimuths can be equipped with Traffic Alert and Collision Avoidance System (TCAS) and ADS-B avionics to reduce spectrum usage and maintain the high surveillance update rate (~1 per second) achieved by ADS-B. Recurring costs for SSPAR will be low since it involves no moving parts and the number of array channels is small. This report describes an SSPAR configuration supporting terminal operations. We consider interrogation and receive approaches, antenna array configuration, signal processing and preliminary performance analysis. An analysis of SSPAR's impact on spectrum congestion in the beacon radar band is presented, as are concepts for integrating SSPAR and next generation primary radar to improve the efficiency and accuracy of aircraft and weather surveillance.
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Summary

The U.S. Federal Aviation Administration is deploying Automatic Dependent Surveillance-Broadcast (ADS-B) to provide next-generation surveillance derived through down- and cross-link of global positioning satellite (GPS) navigation data. While ADS-B will be the primary future surveillance system, FAA recognizes that backup surveillance capabilities must be provided to assure that air traffic...

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Due regard encounter model version 1.0

Published in:
MIT Lincoln Laboratory Report ATC-397

Summary

Airspace encounter models describe encounter situations that may occur between aircraft in the airspace and are a critical component of safety assessment of sense and avoid (SAA) systems for Unmanned Aircraft Systems (UASs). Some UAS will fly in international airspace under due regard and may encounter other aircraft during these operations. In these types of encounters, the intruder aircraft is likely receiving air traffic control (ATC) services, but the UAS is not. Thus, there is a need for a due regard encounter model that can be used to generate these types of encounters. This report describes the development of a due regard encounter model. In order to build the model, Lincoln Laboratory collected data for aircraft flying in international airspace using the Enhanced Traffic Management System (ETMS) data feed that was provided by the Volpe Center. Lincoln processed these data, and extracted important features to construct the model. The model is based on Bayesian networks that represent the probabilistic relationship between variables that describe how aircraft behave. The model is used to construct random aircraft trajectories that are statistically similar to those observed in the airspace. A large collection of encounters generated from an airspace encounter model can be used to evaluate the performance of a SAA system against encounter situations representative of those expected to actually occur in the airspace. Lincoln Laboratory has previously developed several other encounter models. There is an uncorrelated encounter model that is used to generate encounters with an intruder that does not have a transponder, or between two aircraft using a Mode A code of 1200 (VFR). There is also a correlated encounter model that is used when both aircraft have a transponder and at least one aircraft is in contact with ATC. Both of these models were built from radar data collected from the National Airspace System (NAS). There is also an unconventional encounter model that is used to generate encounters with unconventional intruders such as gliders, balloons, and airships--these vehicles have different flight characteristics than conventional aircraft. The framework used to construct the due regard encounter model described in this paper is similar to the prior models. The primary difference is that a different data feed is used and the model covers encounters in international flight where the aircraft of interest is flying due regard, which were not within the scope of prior models. Separate electronic files are available from Lincoln Laboratory that contain the statistical data required to generate encounter trajectories.
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Summary

Airspace encounter models describe encounter situations that may occur between aircraft in the airspace and are a critical component of safety assessment of sense and avoid (SAA) systems for Unmanned Aircraft Systems (UASs). Some UAS will fly in international airspace under due regard and may encounter other aircraft during these...

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Sector workload model for benefits analysis and convective weather capacity prediction

Published in:
10th USA/Europe Air Traffic Management Research and Development Sem., ATM 2013, 10-13 June 2013.

Summary

En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because it does not account for conflicts and recurring tasks. Because of those omissions it cannot be used for accurate benefits analysis of workload-reduction initiatives, nor can it be extended to estimate capacity when hazardous weather increases the intensity of all workload types. We have previously reported on an improved model that accounts for all workload types and can be extended to handle hazardous weather. In this paper we present the results of a recent regression of that model using an extensive database of peak traffic counts for all United States en route sectors. The resulting fit quality confirms the workload basis of en route capacity. Because the model has excess degrees of freedom, the regression process returns multiple parameter combinations with nearly identical sector capacities. We analyze the impact of this ambiguity when using the model to quantify the benefits of workload reduction proposals. We also describe recent modifications to the weather-impacted version of the model to provide a more stable normalized capacity measure. We conclude with an illustration of its potential application to operational sector capacity forecasts in hazardous weather.
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Summary

En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because...

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