Unmanned Aeronautical System (UAS) technology will have to advance within the next five to ten years in order for a successful transition into the National Airspace System (NAS).  Safety, size, and automation are three areas for advancement of UAS technology.  However, improvements in the Federal Aviation Administration (FAA) regulations must simultaneously improve with technology. 

As is the case with all operations in the NAS, safety is paramount. Manned operations allow for the luxury of more situational awareness and have a history and known level of risk.  Unmanned operations pose a new, unique risk for NAS operations and must accommodate for the lack of situational awareness.  In order to do this, UASs must incorporate systems similar to those standardized in manned aircraft.  Automatic Dependent Surveillance Broadcast (ADS-B), Identification Friend-or-Foe (IFF), and Traffic Collision Avoidance System (TCAS) are systems with capabilities that must propagate into all unmanned operations before higher class airspace can be opened to those UASs. However, researchers must note that these systems are not simply one-for-one swaps from manned to unmanned aircraft (Zeitlin & McLaughlin, 2006).  Technology must be developed to incorporate the capabilities in the unique platforms and scenarios that UASs introduce, such as size limitations.

Size is an important limitation that UASs face.  The platform size alone reduces the types of sensors, safety equipment, and overall power available to the system.  Since one of the benefits of UAS is the small size, focus must be placed on creating smaller sensors and safety equipment alongside improved power plants.  As power sources become smaller while maintaining output and efficiency, multiple pieces of equipment can be supported with a smaller size power source.  Moreover, more sensors or pieces of safety equipment could then take the leftover space from the new and improved power plant.  UAS will always face questions concerning the choices of what sensors or systems to include and what platform to use.  As UASs begin to more closely resemble a Mr. Potato Head, producers will have more choices; these choices begin with decreased size requirements.

Finally, a hot button issue concerning UAS operations is automation.  UAS automation has a growing fan base, but safety considerations must take priority.  Certain situations may place the cart before the horse in terms of technological advancements.  The FAA has the ability to regulate the introduction of UAS automation in the NAS. Currently, UAS operation is limited to 400 feet Above Ground Level (AGL) unless within 400 feet of a structure. Additionally, UAS operations are limited to daylight only operations within Class G Airspace unless granted ATC permission (FAA News, 2016). As UAS in the NAS proves itself and its capability of safe operations, automation can increase accordingly.

FAA. (2016). Summary of small unmanned aircraft rule (part 107). Federal Aviation Administration. Retrieved from https://www.faa.gov/uas/media/Part_107_Summary.pdf

Zeitlin, A. D., & McLaughlin, M. P. (2006). Modeling for UAS collision avoidance. MITRE. Retrieved from https://www.mitre.org/sites/default/files/pdf/06_1008.pdf

UAS Use

One area facing rapid growth and change from the rise of UAS is environmental research.  Many areas and types of research are volatile and require UAS support to ensure safety.  Other types of research are the opposite, and require UAS because the environment is too fragile.  Many times the latter, environmental research and research focused on animals can be too difficult for manned assets or personnel to perform alone.  For these reasons, biologists, ecologists, and other researchers have embraced the development of UAS in their fields. 

In November of 2015, four researchers published their results from a 2011 excursion to Antarctica to explore the world of penguins without the help of Morgan Freeman.  Perryman, Gardner, LeRoi, and Ash (2011) were able to utilize three UASs to gather data on thousands of penguins without hindering their behavior or intruding on their ways of life.  The utilization of UASs allowed the researchers to collect data that would have been much more difficult to do with traditional methods.  Most commonly, researchers must move en masse to the penguins to film and document, hopefully able to gather an angle that will allow them to break out the numbers later (or they'd have to estimate).  More importantly, the scientists could depend on the quality of the data without worrying about their affect on the penguins' activities.  For example, the relatively quiet nature of the UAS and the zoom provided by the sensors allowed for imagery and the ability to individually count numbers of penguins. 


Figure 1. Imagery Used to Count Penguins

Additionally, the researchers noted that they were able to collect data on other targets, as opposed to just the penguins.  Specific examples include monitoring movements of seals and measurements of those seals.  Previous research would pose no only a threat to researchers in such a harsh environment, but size alone would prove difficult for the accurate measurement of the creatures. Previous researchers required crews to tranquilize animals to be able to accurately measure them in teams of 2-3 personnel.  Luckily, the UAS provided the ability to both count penguins and measure seal sizes, sometimes during the same missions. 

Figure 2. Imagery Measurement of Seals

The UAS utilization performed by the researchers demonstrates a robust and new capability available to researchers across the globe.  This article provides a peek behind the curtain of things to come in both research and the UAS community in terms of platform and sensor development and environmental uses. 

Sources
Perryman, W., Ash, LCDR N., LeRoi, D., Gardner, S., Goebel, M. Evaluation of small unmanned aerial systems as tools for assessment of krill predators in the Antarctic-final report. (2015). National Oceanic and Atmospheric Administration, 23. Retrieved from https://swfsc.noaa.gov/textblock.aspx?Division=PRD&ParentMenuId=211&id=18412. 

Module 2: Lost Link in the NAS

Unmanned aerial systems (UAS) pose numerous problems within the National Airspace System (NAS).  For these reasons, the Federal Aviation Administration (FAA) has put forth legislation to maintain safety in the NAS after the introduction of UAS.  One of the most difficult problems facing a UAS is the loss of a control data link, commonly referred to as “lost link”.  The International Civil Aviation Organization (ICAO) defines lost link as “The loss of command and control link contact with the remotely-piloted aircraft such that the remote pilot can no longer manage the aircraft’s flight” (ICAO, 2011).  In the event of a lost link, the risk associated with the unmanned operation suddenly increases, possibly placing manned aircraft in harm’s way.

Legislative requirements for UAS in the NAS were discussed in the first edition of the FAA’s roadmap in 2013.  Among those requirements, a goal was set to develop training requirements specific to the lost link requirements that would continue developing through 2020.  Furthermore, the FAA indicated that it would prefer to have UAS training for ATC facilities through 2020 to educate operators on lost link procedures (FAA, 2013, p. 61).  

            The FAA mandated that all unmanned assets except model aircraft operations must provide ATC with lost link procedures in their simplest form.  Additionally, ATC must be able to contact the pilot in command of the UAS.  The aircraft’s technological capability must also include a transponder. One of the most commonly known methods of expressing an emergency in flight, the FAA also requires UAS with lost link to squawk transponder code 7600 (FAA, 2015, p. 4).  

            Although the FAA allows UAS operations within Class A, C, D, E, and G airspace, further guidance was developed for Class C airspace specifically.  Aside from the previous information, the UAS lost link procedures delivered to the FAA must include the “lost link route of flight, transponder us, lost link orbit points, communications procedures, and pre-planned flight termination points in the event recovery of the UAS is not feasible” (FAA, 2011, p. 5). 

            Due to the nature of military UAS operations in Afghanistan, Iraq, and Syria in 2016, lost link occurs often.  Unlike the NAS, however, military UAS have been operating longer and within more understood confines, in addition to (usually) more open airspace.  With the integration of the UAS into the NAS, safety is the primary concern and lost link will pose a great risk to that safety.  Without a doubt, lost link procedures and legislation will continue to be developed indefinitely.

References

FAA. (2011). N JO 7210.766: Unmanned aircraft operations in the national airspace system (NAS). Federal Aviation Administration. Retrieved from http://www.faa.gov/documentlibrary/media/notice/N7210.766.pdf

FAA. (2013). Integration of civil unmanned aircraft systems (UAS) in the national airspace system (NAS) roadmap. Federal Aviation Administration. Retrieved from https://www.faa.gov/uas/media/uas_roadmap_2013.pdf

FAA. (2015). N JO 7210.889: Unmanned aircraft operations in the national airspace system. Federal Aviation Administration. Retrieved from https://www.faa.gov/documentLibrary/media/Notice/N_JO_7210.889_Unmanned_Aircraft_Operations_in_the_NAS.pdf

ICAO. (2011). Circular 328 AN/190: Unmanned aircraft systems (UAS). International Civil Aviation Organization. Retrieved from http://www.icao.int/Meetings/UAS/Documents/Circular%20328_en.pdf

Module 1

For decades, military UAS missions have attempted to collect information against adversaries using tactics, techniques, and procedures (TTPs) to hinder that collection.  Camouflage, concealment, and deception practices often keep enemy weapons and equipment well hidden.  In a technological struggle, however, the U.S. military has developed sensors that mitigate those practices. In turn, the American public and civilian UAS community has and will continue to reap the benefits of that technology in the form of agricultural advancement.

UAS in agriculture is commonplace and researchers have used UAVs to remotely monitor vegetation (Mitchell et al., 2012), map agricultural areas (Everaerts, 2008), and assess rangeland (Rango et al., 2009).  Companies like CropCam use GPS waypoints, elevations, and other parameters to image agricultural land.  The high resolution imagery produced by CropCam and allows farmers to “check seed coverage, gauge irrigation effectiveness, and spot early signs of insect infestation” (Gantenbein, 2009, p. 1).  Previously, farmers would pay upwards of $6,000 for a survey of 1,500 acres of land by a private company. The benefits are enormous for farmers and are reasons why drones are being used for “precision agriculture” (Montopoli, 2013).  However, a step beyond remote monitoring and standard imagery is spectral imagery.

Based on military needs, Raytheon’s Airborne Cueing and Exploitation System – Hyperspectral (ACES-HY) imagery sensor is capable of detecting disturbed earth, chemicals and gasses, explosives and cave entrances (Cheng, 2014). On today’s battlefield, the ACES-HY sensor rides along an MQ-1 Predator and seeks to detect explosive materials amongst all sorts of concealment methods. 

Some researchers have begun to investigate the uses of this type of UAS spectral imagery in agriculture.  Hyperspectral imagery can be utilized within the agricultural community to analyze soil erosion.  As of 2009, the U.S. Geological Survey already incorporated UAS to survey soil erosion (Hruby, 2012).  With an advanced system capable of determining any disturbed earth, the hyperspectral sensor would allow for incredible accuracy in comparison to current technology.  Turner, Lucieer, and Watson (2011) used multispectral cameras on UAVs to measure plant health.  The sensor analyzed water stress based on the Photochemical Reflectance Index (PRI), which alludes to the overall vigor of grape vines. This type of analysis could change the ways vineyards manage planting, maintenance, and harvesting by pinpointing where extra fertilizer or pesticide might be needed (Reed, 2012).  Furthermore, this type of analysis could change global agriculture altogether.

 Figure 1. Oktokopter fitted with multispectral camera.

References

Cheng, J. (2014). Hyperspectral sensor lets drones see through camouflage, spot explosives. Defense Systems. Retrieved from https://defensesystems.com/articles/2014/02/25/air-force-aces-hy-hyperspectral.aspx?admgarea=DS    

Everaerts, J. (2008). The use of unmanned aerial vehicles (UAVs) for remote sensing and mapping. The International Archives of the Photogrammetry: Remote Sensing and Spatial Information Sciences, 37. Retrieved from https://www.google.ae/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwiOxa3N1cPOAhUJaRQKHUnMAP4QFggfMAA&url=http%3A%2F%2Fwww.isprs.org%2Fproceedings%2FXXXVII%2Fcongress%2F1_pdf%2F203.pdf&usg=AFQjCNE_ogqstURtMFrzjUccV1WFDygG5g

Gantenbein, D. (2009). Unmanned traffic jam. Air & Space Magazine. Retrieved from http://www.airspacemag.com/flight-today/unmanned-traffic-jam-137094132/?no-ist=&page=2

Hruby, P. (2012). Out of ‘hobby’ class, drones lifting off for personal, commercial use. The Washington Times. Retrieved from http://www.washingtontimes.com/news/2012/mar/14/out-of-hobby-class-drones-lifting-off-for-personal/

Mitchell, J. J., Glenn, N. F., Anderson, M. A., Hruska, R. C., Halford, A., Baun, C., & Nydegger, N. (2012). Unmanned aerial vehicle (UAV) hyperspectral remote sensing for dryland vegetation monitoring. Journal of Applied Remote Sensing, 3(1), 1-10. Retrieved from https://www.google.ae/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjlsJeL1MPOAhXHBBoKHXw3DQ8QFggeMAA&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6874315&usg=AFQjCNEvtCYjqd5kblHkbAw8vt4YoMJpSA

Montopoli, B. (2013). The drone next door. CBS News. Retrieved from http://www.cbsnews.com/news/the-drone-next-door/

Rango, A., Laliberte, A., Herrick, J. E., Winters, C., Havstad, K., Steele, C., & Browning, D. (2009). Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management.  Journal of Applied Remote Sensing, 3(1), 1-15. Retrieved from https://www.google.ae/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwiA5pSA1cPOAhXFExoKHWN7DbcQFggdMAA&url=https%3A%2F%2Fwww.ars.usda.gov%2FSP2UserFiles%2FPlace%2F30501000%2FUnmanned.pdf&usg=AFQjCNEX9BL7PgqZIPmcu5XvT5-zCf0z0A

Reed, J. (2012). The skies open up for large civilian drones. BBC News. Retrieved from http://www.bbc.com/news/technology-19397816

Turner, D., Lucieer, A., & Watson, C. (2011). Development of an unmanned aerial vehicle (UAV) for hyper resolution vineyard mapping based on visible, multispectral, and thermal imagery. International Symposium on Remote Sensing of Environment  2011. Sydney. https://www.google.ae/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwi495C50sPOAhWEOxQKHadHAg0QFggaMAA&url=http%3A%2F%2Fwww.isprs.org%2Fproceedings%2F2011%2FISRSE-34%2F211104015Final00547.pdf&usg=AFQjCNE_QfmdXuObyp25umDCqCUPNOg2IQ