Course: Unmanned Aerospace Systems Operations & Payload
An Unmanned Aerial Systems (UAS) is essentially an integrated set of components, parts and technological elements and mechanisms which is designed for the purpose of flight but is not directly operated by a human. They can be used within a broad set of applications including site inspections, rescue missions and air-to-air combat. They present tremendous advantages which include increased safety factors, lower development and operational costs, and rapid deployability. The use of UAS have been growing exponentially. Teal Group predicts worldwide military UAS production of ninety billion over the next decade (Teal Group Corporation, 2018). The Federal Aviation Administration (F.A.A.) forecasted small, hobbyist UAS to grow from 1.9 million in 2016 to as many as 4.3 million by 2020 (F.A.A, 2016). Such a tremendous rise in usage has rendered necessary the need to fully integrate UAS in national airspaces. Integrating UAS in the national airspace present significant challenges which include the development of more advanced technologies such as detect and avoid systems, command-and-control links, security systems and communication frequency spectrum. It will also require the development of improved pilot operators qualifications programs and new privacy policies (Oliver, 2016). Given such challenges, what are the latest development in UAS detect and avoid systems?
UAS Detect and Avoid systems essentially encompass guidance and navigations, camera and radars, vehicle command and control, situational awareness, light detection and ranging (LIDAR) sensors, obstacle avoidance and automated trajectory corrections applications. UAS are generally built with data centric principles where information flow through sensing, planning, control, and safety command modules (Schneider, n.d.). Dataflow security algorithms are built to ensure system safety and prevent incidents. The planning module functions include monitoring vehicle and potential obstacle positioning and issuing a warning in case of a potential threat. The control module functions include monitoring positioning of the vehicle and any potential obstacle and issuing commands that correct the UAS trajectory and prevent a potential collision. The safety module functions also include situational awareness and threat mitigation maneuvers (Schneider, n.d.). This is significant because it highlights UAS manufacturing and design readiness to achieve a seamless integration. It also supports the current trends and development which essentially constitute of UAS systems improvements, manned aircraft and infrastructures mitigation strategies and the drafting of usage policies to sustain the prevention of incidents.
The requirements specified in title 14 of the code of federal regulations are very broad and not specifically derived for UAS. It highlights the deficiencies, flaws and limitations being faced by regulatory agencies due to sets of assumptions, theories and “fuzzy logics” challenged by the scope of UAS flight. The reality is that UAS are generally a novelty with rapidly growing technologies which renders challenging the establishment of robust usage procedures and policies. Despite these circumstances, significant progress is being made by UAS manufacturers, aircraft and aerial infrastructures designers and global regulatory agencies. The most intriguing development in UAS Detect and Avoid systems include a fast geometric algorithm (FGA) and the use of unconventional visual sensors for vision-based navigation. FGA is essentially a 3D rapid collision avoidance algorithm that is essentially based on an optimization and prediction of UAS and potential obstacle positions. It uses 3 dimensional positional coordinates to rapidly compute and predict systems and obstacle positions with respect to incremental time intervals similarly to a Brownian or Lagrangian function. It then rapidly develops and select the most efficient trajectory correction for the UAS which is based on avoiding collision with the detected systems (Lin et al., 2020). Unconventional visual sensors are also another set of fascinating technologies. They include event-based cameras, range cameras and light field cameras. Event-based cameras’ advantages reportedly include low temporal latency, high dynamic range, and a very low bandwidth requirement (Bijjahalli et al., 2020).
As it pertains to development from regulatory agencies and air traffic management, the concept of a hierarchical UAS traffic management may prove very efficient. It is essentially built on the principles of safety and interoperability exhibited by platform such as NexGen and SESAR. But here, UAS are specifically monitored by size, weight and thrust capabilities. UAS flying under 400 feet are assigned to a local or regional traffic management unit. The flight paths of UAS flying above 400 feet are computed and thoroughly monitored. Flight paths priorities are assigned to all aircraft types. In case of a potential collision flagged by the internal flight monitoring algorithm or system, both autonomous and remotely piloted UAS can be sent collision avoidance commands which are often trajectory correction maneuvers (Lin & Shao, 2020).
References
Bijjahalli, S., Sabatini, R., & Gardi, A. (2020). Advances in Intelligent and Autonomous
Navigation Systems for Small UAS. Progress in Aerospace Sciences, 115,
100617. https://doi.org/10.1016/j.paerosci.2020.100617
Federal Aviation Administration.(2016, March 24). FAA Releases 2016 to 2036 Aerospace
Forecast. Retrieved from https://www.faa.gov/news/updates/?newsId=85227
Lin, C. E., & Shao, P. C. (2020). Development of Hierarchical UAS Traffic Management (UTM) in
Taiwan. Journal of Physics. Conference Series, 1509(1), 12012.
https://doi.org/10.1088/1742-6596/1509/1/012012
Lin, Z., Castano, L., Mortimer, E., & Xu, H. (2020). Fast 3D Collision Avoidance Algorithm for
Fixed Wing UAS. Journal of Intelligent & Robotic Systems, 97(3-4), 577-604.
https://doi.org/10.1007/s10846-019-01037-7
Oliver, J. (2016). Routine Unmanned Aircraft Systems Operations in the National Airspace
System: Benefits and Challenges. TR News, (304). Schneider S. (n.d.). The Secret Sauce
of Autonomous Cars.
https://info.rti.com/hubfs/whitepapers/Secret_Sauce_of_Autonomous_Cars.pdf
Teal Group Corporation. (2018, November 19). Teal Group Predicts Worldwide Military UAV
Production of $90 Billion Over the Next Decade [Press Release]. Retrieved from
worldwide-military-uav-production-of-90-billion-over-the-next-decade
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