Investigating Detect-and-Avoid Surveillance Performance for Unmanned Aircraft Systems

Park, Chunki; Lee, Seung Man; Mueller, Eric R.

doi:10.2514/6.2014-2413

Cited by 8 publications

(3 citation statements)

References 7 publications

(7 reference statements)

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“…Due to the similarity of trajectory models used for large-size fixed-wing UASs and manned fixed-wing aircraft, the latest ACES incorporated models of large fixed-wing UASs 8 in order to study interactions between Unmanned Aircraft Systems(UAS) and manned aircraft. 9,10 In addition to these large aircraft simulation tools, researchers often developed their own simulation tools for specific research topics. For instance, Cook et.…”

Section: Literature Reviewmentioning

confidence: 99%

Initial Study of An Effective Fast-time Simulation Platform for Unmanned Aircraft System Traffic Management

Xue

Rios

2017

17th AIAA Aviation Technology, Integration, and Operations Conference

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Small unmanned aircraft systems are envisioned to play a major role in surveilling critical assets, collecting data, and delivering goods. Large scale operations are expected to happen in low altitude airspace in the near future, where many static and dynamic constraints exist. High sensitivity to wind and high maneuverability are unique characteristics of these vehicles, which bring great challenges to effective system evaluations and mandate such a simulation platform different from existing simulations that were built for manned air traffic system and large unmanned fixed-wing aircraft. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative focuses on enabling fair, safe, and efficient unmanned aircraft system operations in the future. In order to help define requirements and policies for a safe and efficient UTM system to accommodate a large amount of unmanned aerial vehicle operations, it is necessary to develop a fast-time simulation platform that can effectively evaluate policies and concepts, and perform parameter studies in a close-to-reality environment. This work analyzed the impacts of some key factors and demonstrated the importance of these factors in a successful UTM fast-time simulation platform. Preliminary experiments were also conducted to show potentail applications of such a platform. I. IntroductionThe volume of small Unmanned Aircraft System(sUAS) operations is expected to increase dramatically in the near future. 1 Potential sUAS applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. According to the marketing analysis 2 , the global small UAS market is anticipated to hit 10 billion by 2020. FAA also forecasted that over 7 million sUASs will be sold annually by 2020. 1 The sUAS's low operational altitude, small size, and envisioned scale of operations make Unmanned aircraft system Traffic Management (UTM) quite different from conventional aviation traffic management. In the low altitude airspace, besides fast-changing wind conditions, restricted areas, manned aircraft/helicopters, and tall buildings/terrain impose many constraints in sUAS operations. The sensitive trajectory response and high maneuverability make sUAS different from manned or unmanned large-size fixed-wing aircraft and dramatically change the way traffic system operates. These characteristics and the predicted large scale operations 1 present great challenges in managing safe and efficient traffic operations in low altitude airspace.NASA's UTM research initiative 3, 4 is researching and defining requirements and policies for the UTM system to ensure fair, safe, and efficient UAS operations in the future. In order to investigate the impacts of various device parameters, traffic system rules and policies, operational schedules, and wind conditions, especially in dense operations, it is necessary to build an effective fast-time simulation platform that can incorporate different parameters, rules, ...

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Section: Literature Reviewmentioning

confidence: 99%

Initial Study of An Effective Fast-time Simulation Platform for Unmanned Aircraft System Traffic Management

Xue

Rios

2017

17th AIAA Aviation Technology, Integration, and Operations Conference

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“…According to Zeitlin [27], performances of a sensor can be described by five variables: field of regard (FOR), range, update rate, accuracy, integrity; we add a sixth important variable: safety. In a study on sensor's range and field of regard, Park et al [28] showed that with a horizontal FOR of ±90 horizontally, ±20 vertically and a range of 10NM, more than 90% of the aircraft could be detected 60 seconds before loss of separation. They also mention that a sensor with high vertical FOR, about 65 , and short range, about 2NM, could detect all intruders at the latest when loss of separation occurs.…”

Section: A Performancesmentioning

confidence: 99%

An introduction to ACAS Xu and the challenges ahead

Manfredi

Jestin

2016

2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC)

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“…For the remainder of this section, this approach is referred to as the "NASA encounter model". It has been used to conduct several foundational NAS-wide and parametric fast-time simulations in support of MOPS development [8,[11][12][13][14][15].…”

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confidence: 99%

Encounter-Based Simulation Architecture for Detect-And-Avoid Modeling

Refai¹,

Abramson²,

Lee³

et al. 2019

AIAA Scitech 2019 Forum

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This paper presents an encounter-based simulation architecture developed to facilitate flexible and efficient detect and avoid modeling in parametric or trade-space studies on large data sets. The basic premise of this tool is that large-scale input data can be reduced to a set of "canonical encounters" and that using the reduced data in simulations does not lead to loss of fidelity. A canonical encounter is specified as ownship and intruder flight portions potentially resulting in a loss of well clear along with a set of properties that characterize the encounter. The advantages of using canonical encounters include faster simulations, reduced memory footprint, ability to select encounters based on user-specified criteria, shared encounters across multiple teams, peer-reviewed encounters, and a better understanding of the input data set, to name a few. The performance of the encounter-based approach is compared to the approach used previously, which modeled flights from departure to destination using the Java Architecture for DAA Extensibility and Modeling (JADEM). The new architecture reduced the amount of data to be processed a hundredfold and the total computation time five-fold.

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Investigating Detect-and-Avoid Surveillance Performance for Unmanned Aircraft Systems

Cited by 8 publications

References 7 publications

Initial Study of An Effective Fast-time Simulation Platform for Unmanned Aircraft System Traffic Management

Initial Study of An Effective Fast-time Simulation Platform for Unmanned Aircraft System Traffic Management

An introduction to ACAS Xu and the challenges ahead

Encounter-Based Simulation Architecture for Detect-And-Avoid Modeling

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