ASCI 530 Blog Post 5: Response to Request for Proposal

Small Unmanned Aerial Systems (sUAS) can provide valuable intelligence in support of disaster response. In a quickly deployable package, they can be launched to expand the coverage area of search parties, collect critical data prior to conducting specific rescue or firefighting tasks, and survey damages. In areas with complex terrain and poor visibility, sUAS may be the only option for aerial data collection. The following paper will explore the requirements derivation process for a disaster response sUAS.

Mission

The proposed sUAS will be primarily marketed towards law enforcement, firefighting, and other crisis response organizations as a solution for man-portable tactical reconnaissance. Fire Apparatus identifies DJI and FireFly UAS as the most prevalent in fire fighting use (Petrillo, 2016), which the new vehicle aims to replace through superior performance. It will be designed around the following core tasks:

• Identifying distressed persons
• Characterizing compromised structures
• Surveying damage and safety hazards
• Providing situational awareness to distributed team members

Base Requirements

The Request for Proposal (RFP) contained baseline requirements for transportability, cost, air vehicle element, command and control element, payload, datalink, and support equipment. Three will be broken down into derived requirements. 

Payload

5.1 Shall be capable of color daytime video operation up to 500 feet AGL

     5.1.1 Shall provide 90% probability of recognition in clear daytime lighting conditions between one hour after sunrise until one hour prior to sunset.

     5.1.2 Shall provide 90% probability of detection in degraded conditions defined as lighting within one hour of sunrise/sunset, haze, light fog, smoke, and dust.

     5.1.3 Shall meet 5.1.1 and 5.1.2 criteria at a slant range of 700 feet.

5.2 Shall be capable of infrared (IR) video operation up to 500 feet AGL

     5.2.1 Shall provide 90% probability of recognition in unobscured atmospheric conditions outside of the thermal crossover period (within one hour of sunrise/sunset).

     5.2.2 Shall provide 90% probability of detection in degraded conditions defined as the thermal crossover period, haze, light fog, smoke, and dust.

     5.2.3 Shall meet 5.1.1 and 5.1.2 criteria at a slant range of 700 feet.

5.3 Shall be interoperable with C2 and data-link

     5.3.1 Shall receive uplinked commands from the air vehicle using RS-232 interface.

     5.3.2 Shall return feedback/status messages to the air vehicle using RS-232 interface.

     5.3.3 Shall compress time-stamped sensor metadata and raw video into H.264/AVC compliant transport stream (MISB, 2010).

     5.3.4 Shall export compressed video via RS-422 interface to air vehicle transmitter.

5.4 Shall use power provided by air vehicle element

     5.4.1 Shall operate from 22.2VDC power source.

     5.4.2 Shall not exceed 1,000mAh power consumption in any mode of operation.

Datalink

6.1 Shall be capable of communication range exceeding two miles line of sight (LOS)

     6.1.1 The air vehicle and controller shall automatically detect co-channel interference.

     6.1.2 Upon detecting co-channel interference, the air vehicle and controller shall automatically switch frequencies within 500ms.

6.2 Shall provide redundant communication capability (backup) for C2

     6.2.1 Shall have a primary Frequency Hopping Spread Spectrum (FHSS) Federal Communications Commission (FCC) compliant S-band datalink.

     6.2.2 Shall have a secondary Frequency Hopping Spread Spectrum (FHSS) Federal Communications Commission (FCC) compliant UHF-band datalink.

6.3 Shall use power provided by air vehicle element 

     6.3.1 Shall operate from 22.2VDC power source.

     6.3.2 Shall not exceed 2,500mAh power consumption in any mode of operation.

Support Equipment

7.1 Design shall identify any support equipment required to support operation 

     7.1.1 Shall include a 115VAC field battery charger capable of charging two batteries in one hour.

     7.1.2 The vehicle shall save recorded photos on a removable Secure Digital Extended Capacity (SDXC) card in JPEG format.

     7.1.3 The vehicle shall save recorded videos on a removable Secure Digital Extended Capacity (SDXC) card in MPEG-4 format.

Design Overview

Fielding the tactical crisis response sUAS will be largely an integration effort between several mature technologies. The vehicle will be a tilt-wing configuration with four wingtip electric motors turning fixed pitch propellers. This blends the rotary wing ability to takeoff/land vertically and hover, with the speed and endurance of a fixed wing. The payload will be similar to the combined electro-optical (EO)/infrared (IR) system under development for the Insitu ScanEagle (Insitu, 2015), providing greater data on the ground scene on the same sortie without having to modify the vehicle. A key feature for this sUAS will be the capability to stream full-motion video and associated metadata to dispersed ground parties. While many commercially available sUAS are able to distribute video from their control stations via web streaming (ex. YouTube), this service may be unavailable during a crisis as cell networks are damaged or overloaded. The proposed sUAS will transmit its video feed to tablets and smart phones, enabling recovery personnel to share a common operating picture. Onboard flight control will be accomplished by dual redundant sensor and processing modules that will compare outputs prior to sending commands to effectors. To enable high downlink speeds, the primary datalink will use an S-band FHSS protocol. In the event all available S-band channels become unusable, a backup UHF datalink will provide essential control and telemetry functions for safe recovery. The power system will consist of two commonly available 22.2VDC 11,000mAh batteries.  

Test & Evaluation Criteria

Payload

Section 5 requirements can be accomplished independent of vehicle testing in an enclosed facility that provides control of ambient lighting and simulating various visibility conditions. In order to expand the operational field of regard, all sensor requirements will need to be satisfied at a slant range of 700 feet (equates to a 45 degrees sensor depression angle). Sensor fidelity will be tested using the U.S. Air Force Equivalent Bar Chart, which establishes a normalized, objective means of determining if a sensor can be expected to meet certain thresholds (McShea, 2010).

5.1.1 Illumination will be varied from 10.8-10752 Lux (average twilight to full daylight) to meet the “recognition” threshold (object is present and can be classified) to 90% certainty.

5.1.2 The EO sensor fidelity will be tested in degraded conditions from 10.8-1.08 (average twilight to deep twilight) in artificial fog down to visibilities of 2 miles, to meet the “detection” threshold (object is present) to 90% certainty. It will be assumed that the vehicle will not be operated beyond visual line of sight.

5.2.1-3 The IR sensor fidelity will be tested similarly to the EO sensor, with average bar target radiances varied 200-500 degrees Kelvin.

5.3 All of these requirements can be tested concurrently with 5.1 and 5.2 by connecting the sensor to RS-232 and RS-422 compatible receivers with H.264/AVC video decoding software and displayed.

5.4 The payload will be exercised to worst-case conditions, as determined through analysis of individual subcomponent current requirements. Measurements will be recorded and multiplied by a safety factor of 25%.

Datalink

All datalink requirements will be tested using a production-ready article (to identify any electro-magnetic interference in the final design) placed in an anechoic chamber equipped with precision transmitters and frequency controllers.

6.1 The vehicle will be operated in a representative manor while a specific S-band frequency is jammed. The UAS’s FHSS algorithms should skip to alternate frequencies, with no interruptions to control or downlinked video observed by the operator.

6.2 The vehicle will be operated in a representative manor until broadband S-band noise is injected. The UAS should automatically transition to the backup UHF datalink, with no apparent loss of control observed by the operator (loss of downlinked video is acceptable).

6.3 The datalink will be exercised to worst-case conditions, as determined through analysis of individual subcomponent current requirements. Measurements will be recorded and multiplied by a safety factor of 25%.

Support Equipment

Support equipment requirements can be tested concurrently with other developmental test events.

7.1 The suitability of the battery charger can be tested as soon as a design decision is made on the specific battery. Since the support equipment should exhibit a high degree of reliability for first responders, criteria provided in MIL-STD-810 Environmental Engineering Considerations and Laboratory Tests should be followed while measuring charging times.

7.2-3 As soon as a complete system is assembled, media recording can be verified concurrently with other events. After each flight, files on the SD card should be checked for time stamp errors and corruption.

Development Process

The Rapid Application Development (RAD)(OIS, 2008) model will be used to accelerate the “10 Phases of Development” (Austin, 2010). Since a conceptual design has already been established based on similar products, the process will begin with preliminary design. This phase, along with detailed design, prototyping, and test are forecasted to take three years (roughly half of Austin’s recommendation) due to low technical risk and the use of Concurrent Development (CD). CD compresses development timelines by simultaneously completing multiple phases of the acquisition process. In this case, development of the vehicle and payload will run in parallel, which makes interface control a key focus area. Prototyping and early flight test can also overlap to identify and correct any deficiencies as early as possible. The certification process will also start one year prior to fielding. While a production-representative article may not be available at that point, certification can be started on the premise of similarity with other certified systems, contingent on final verification results. A Gantt Chart will be used to track progress, manage resources, and maintain timelines. The team will also employ Agile Manufacturing principles (Sarhadi, Gunasekaran, & Yusuf, 1999) to accelerate the prototyping, production, and support phases, by leveraging Computer Assisted Drafting (CAD) and 3-Dimensional printing for example.

References

Austin, R. (2010). Unmanned aircraft systems: UAVs design, development and deployment. Reston, VA: American Institute of Aeronautics and Astronautics.

Insitu. (2015). ScanEagle Product Card. Retrieved November 22, 2016, from https://insitu.com/images/uploads/pdfs/ScanEagle_SubFolder_Digital_PR080315.pdf

McShea, R. E. (2010). Test and evaluation of aircraft avionics and weapon systems. Raleigh, NC: SciTech Pub.

Motion Imagery Standards Board. (2010). Constructing a MISP Compliant File/Stream (MISB TRM 0909.2).

Petrillo, A. (2016, July 6). Drones Poised to Be Used on More Fire Scenes Across the United States. Retrieved November 30, 2016, from http://www.fireapparatusmagazine.com/articles/print/volume-21/issue-6/features/drones-poised-to-be-used-on-more-fire-scenes-across-the-united-states.html

Office of Information Services. (2008). Selecting a Development Approach (United States, Department of Health and Human Services, Center for MEDICARE & MEDICAID Services).

Sarhadi, M., Gunasekaran, A., & Yusuf, Y. Y. (1999). Agile manufacturing:: The drivers, concepts and attributes. International Journal of Production Economics, 62(1), 33-43. doi:10.1016/S0925-5273(98)00219-9

ASCI 530 Blog Post 4: UAS Missions - Disaster Response

Military support from active and national guard forces is critical for disaster response efforts, as it allows civil entities access to manpower and equipment normally reserved for defense. Specifically, Combat Search and Rescue (CSAR) forces can be leveraged to find, recover, and treat distressed persons, which was used extensively following Hurricane Katrina. The Air Force alone generated over 1,700 airlift, strategic reconnaissance, and rescue helicopter sorties for the recovery effort (Ball, 2016). An absent capability was tactical reconnaissance, which could have been used to efficiently identify and prioritize victims, and provide locations for rescue crews. With several National Guard units converting to various Unmanned Aerial Systems (UAS), this capability could be included in future domestic disaster relief efforts.

Figure 1. US Air Force CSAR unit recovers flood victims from a rooftop. Reprinted from Air Force Reserve Command Citizen Airman Magazine, 2005.

The Mission

Tactical reconnaissance, in the context of disaster response, provides area searches, precise point-of-interest geolocation, and continuous near-realtime intelligence. It also involves networking with command centers, directing rescue assets to victims, and surveying helicopter pickup zones. Specific tasks for a UAS include:

• Systematic area searches from low to medium altitudes, using infrared (IR) and electro-optical (EO) sensors to determine the location, disposition, and trend of stranded victims with high fidelity.
• Returning full-motion video high-rate synthetic aperture radar scans to provide realtime status of victims or difficult to observe situations like chemical fires or potentially explosive material.
• Using the communications reach-back inherent in UAS to maintain tactical command and control of rescue assets, direct helicopters to victims, and act as a radio relay.

System Selection

The Boeing-Insitu ScanEagle, General Atomics MQ-1B/C, and General Atomics MQ-9A will be analyzed for suitability in the disaster relief mission. All three systems have been extensively used by the US military, providing a large body of experienced operators and proven track record that can hopefully ease certification for use in the National Airspace System (NAS). The ScanEagle is flown via Line-of-Sight (LOS) control only, whereas the other three can be flown via either LOS or Beyond-Line-of-Sight (BLOS) control.

The ScanEagle is a 49lb low altitude vehicle that is launched with a catapult and recovered by a SkyHook (crane with wire that is snagged by wingtip-mounted hooks). It boasts 24 hour endurance with a cruise speed of 50-60 knots (Insitu, 2015). The payload bay currently accommodates a single EO or IR sensor (dual sensor in development). The ScanEagle range is limited to 62 miles by the LOS data link, meaning that it will have to be transported to a launch/recovery site close to the disaster, losing precious time. The ScanEagle’s lightly loaded, high aspect ratio wing is also highly responsive to turbulence (Austin, 2010), which may be undesirable in the wake of a major meteorological event.

The MQ-1 Predator B and C are medium altitude aircraft weighing 2,200lbs and 3,600lbs respectively (General Atomics, 2016). Both carry a large multi-spectral sensor turret for searches in all lighting conditions. The turrets also include eye safe laser markers that can be used to guide night vision-equipped rescue helicopters to distressed persons, a capability that would have proved useful during the first eight days of Katrina recovery where crews operated around the clock (Ball, 2016). The MQ-1 provides up to 30 hours of endurance and BLOS datalinks allow it to be flown from home base to a disaster area, at a cruise speed of 150 knots to respond quickly.

The MQ-9A Reaper is another medium altitude UAS, weighing over 10,500lbs and bringing similar sensor technology as the MQ-1 (General Atomics, 2016). While the Reaper nearly doubles many MQ-1 performance parameters, it will not significantly enhance the rescue mission. It also requires longer runways and additional support equipment, making it more difficult to forward-deploy than the ScanEagle or Predator.

The MQ-1 Predator is the recommended choice for disaster response in suitability and number, with the Air Force and Army maintaining domestic fleets for training. Additionally, the Army has equipped 10 divisions with MQ-1Cs, adding flexibility through geographical coverage (US Army, 2016).

Legal and Ethical Considerations

The most glaring issue for domestic employment of military MQ-1s is legal, and may appear to be a violation of Title 18 United States Code (USC), Section 1385, commonly known as the Posse Comitatus Act (PCA). Under Title 32 USC, a state governor can “call forth the militia” to respond to civil emergencies and that those forces are not subject to PCA (Elsea & Mason, 2008). This implies that UAS operated by the National Guard (Army or Air Force), as authorized by the Governor, are exempt from PCA. Federal military forces can be legally committed for search and rescue operations under Title 42 USC, Section 5121 (Stafford Act) at the request of the affected state governor. Additionally, Congress has issued standing guidance to the Department of Defense (Title 10 USC, clause 371-382) to share information and equipment with civilian authorities. With this relatively permissive application of the law, ethical concerns may arise with the use of military surveillance aircraft in the NAS. Component commanders need to ensure that UAS operators are not inappropriately using sensors to collect information on citizens and/or property for personal use, or explicitly for criminal prosecution. In the case of the latter, UAS crews scanning private property during recovery efforts shall not devolve into illegal searches under the PCA, or record data for future use.

Conclusion

This short essay has defined a civil use for military UAS, providing three core tasks of search, victim location sharing, and networking. Three platforms were considered, and the MQ-1 (B or C) was selected as the most suitable for disaster relief efforts due to long loiter time, resistance to moderate meteorological phenomena, and relatively small logistical footprint. The legal implications of employing military UAS in support of civil disaster response were analyzed and found to allow their operation. Ethical conduct of such operations was also discussed, with risks mitigated by guidance from component commanders.

References

Austin, R. (2010). Unmanned aircraft systems: UAVs design, development and deployment. Reston, VA: American Institute of Aeronautics and Astronautics.

Ball, G. (2005, November 3). Hurricane Katrina Relief Operations. Retrieved August 22, 2016, from http://www.afhso.af.mil/topics/factsheets/factsheet.asp?id=18651

Elsea, J., & Mason, R. C. (2008). The use of federal troops for disaster assistance: Legal issues (United States). Washington, D.C.: Congressional Research Service, Library of Congress. Retrieved from www.dtic.mil.

General Atomics Aeronautical Systems. (2016). Aircraft Platforms. Retrieved November 22, 2016, from http://www.ga-asi.com/aircraft-platforms

Insitu. (2015). ScanEagle Product Card. Retrieved November 22, 2016, from https://insitu.com/images/uploads/pdfs/ScanEagle_SubFolder_Digital_PR080315.pdf

United States Army. (2016). MQ-1C Gray Eagle Unmanned Aircraft System. Retrieved November 22, 2016, from http://asc.army.mil/web/portfolio-item/aviation_gray-eagle-uas/

ASCI 530 Blog Post 3: UAS in the NAS

As Unmanned Aerial Systems (UAS) become more prevalent in the United States, a safe and effective method of National Airspace System (NAS) integration is needed to prevent stifling the new industry. The method should include Group 1 through 5 UAS and all varieties of aircraft configuration.

Figure 1. US Department of Defense UAS group descriptions. Reprinted from DoD UAS Airspace Integration Plan , by the UAS Task Force, 2011.

Understanding the Problem

The Federal Aviation Administration (FAA) is charged with maintaining control of the NAS, and does so with operating regulations, operator qualifications, and airworthiness certifications (FAA, 2016). The Department of Defense (DoD), commercial, and public research entities require access to the NAS for numerous missions, however FAA regulation has lagged UAS industry growth, creating a roadblock for many military and civil operations. The root of the problem lies in safe traffic separation between manned and unmanned aircraft, all with a wide variety of equipage standards. In airspace classes A and B, responsibility for separation lies with air traffic control (ATC) using primary and secondary radar systems. In airspace classes C through G, a UAS will face the challenge of integrating with optionally or non-participating aircraft. Instrument or visual flight rules (IFR or VFR) overlay additional considerations. Under IFR, aircraft are separated by positive (ATC personnel) or procedural control (published departure, arrival, or approach procedures). Under VFR, pilots are responsible for their own separation, optionally participate with ATC depending on the airspace class, and are the most challenging airspace user for UAS to share with. The following solutions encapsulate a phased approach that starts with systems technologically closer to NAS access and working towards full UAS access.

IFR Solution

This solution is most readily implemented with Group 4 and 5 UAS, as many of them already meet (or have the space and power available for) the IFR equipment requirements in Federal Aviation Regulation (FAR) 91.205 (FAA, 2009). Medium and high altitude UAS would transition to Class A airspace using procedural control measures (such as a climb corridor) recommended by the DoD UAS Integration Task Force (2011) that would separate non-participating manned aircraft by charting the control measures as special use airspace. Once above FL180, UAS would not differ from manned aircraft in operation or control. One UAS specific condition is loss of command and return links. Large UAS have robust lost-link programming capabilities which would be leveraged to maintain the aircraft in a safe and predictable state. In the terminal environment, lost-link UAS would follow a predetermined path similar to a missed approach procedure. During en route phases, lost-link UAS would follow either a path provided in a procedure similar to a Standard Terminal Arrival, or fall back on the same guidance for manned aircraft that lose contact with ATC (maintain last assigned, then expected, then filed). In any case, the burden of ensuring safe lost-link separation would rest with an appropriately trained and certified UAS pilot. This IFR solution has the benefit of requiring very little aircraft modification, can be implemented with today’s technology, and allows large UAS to access the NAS soonest in order to accomplish critical missions and begin adding to the collective knowledge base. The costs are increased workload on air traffic control, administrative functions to create the procedures given above, and establishment of additional Class B airspaces in areas with high UAS traffic.

VFR Solution

A VFR solution would allow UAS access to all airspace classes in the NAS, but is the most difficult to implement technologically. Significant research has been done to allow UAS to satisfy the “see and avoid” FAA requirement for VFR flights. The most successful to date has been demonstration of autonomous and pilot directed collision avoidance using a fusion of Automatic Dependent Surveillance-Broadcast (ADS-B), Traffic Collision Avoidance System (TCAS), and onboard air-to-air radar. This allows separation from close range TCAS-equipped aircraft, close range ADS-B/Out-equipped aircraft with onboard ADS-B/In functions, and non-participating aircraft. Additionally, a UAS equipped with a Universal Access Terminal would receive traffic and weather data from ground stations, adding redundancy. The only shortfall of such an all-inclusive system is the cost in size, weight, and power supply which would exclude Group 3 and below vehicles. UAvionics has marketed a micro ADS-B receiver weighing only 1.5 grams that provides autopilots or ground control stations with participating traffic information within 100 miles (sUAS News, 2016). The most promising solution for separating light UAS from non-participating traffic lies in vision based systems that combine multi-spectral sensors with image processing algorithms to detect moving objects (Novik, 2014). The challenge vision based systems will face is providing the same detection probability as a human pilot in an extremely wide range of ambient lighting and atmospheric conditions. For Group 1 UAS, even vision systems and micro receivers may impose an unacceptable sacrifice in payload. Since they weigh less than 20lbs, a risk analysis should be conducted to determine the probability of collision with manned aircraft and whether the consequences would exceed that of bird strikes.

Conclusion

This short essay has defined the challenging problem of operating manned and unmanned traffic in the NAS in the context of airspace classes and flight rules. The DoD is poised to access the NAS with large UAS, as it has established internal practices to satisfy the technology, training, and certification needed for integration. Rapid integration of these assets will not only accomplish vital defense, training, and disaster response missions, but pave the way for commercial and public operations. Technical solutions for lightweight UAS were summarized, along with the inspiration to conduct risk analysis, since a 100% perfect solution may not be required and will likely constrain development.

References

Federal Aviation Administration. (2016). National Airspace System. Retrieved November 10, 2016, from http://www.faa.gov/air_traffic/nas/

Federal Aviation Administration. (2009, August 21). Federal Aviation Administration. Retrieved November 10, 2016, from http://rgl.faa.gov/Regulatory_and_Guidance_Library/rgFar.nsf/FARSBySectLookup/91.205

Federal Aviation Administration. (2016, May 10). Equip ADS-B Research. Retrieved November 11, 2016, from https://www.faa.gov/nextgen/equipadsb/research/

Merlin, P. (2015, January 25). NASA, FAA, Industry Conduct Initial Sense-and-Avoid Test. Retrieved November 11, 2016, from http://www.nasa.gov/centers/armstrong/Features/acas_xu_paves_the_way.html

Novick, D. (2014, January). Image Processing Primer Document for Autonomous Vehicle Competitions. Retrieved November 11, 2016, from http://www.robotx.org/

SUAS News. (2016). UAvionix Introduces Micro ADS-B Receiver For Small Drone Collision Avoidance - sUAS News. Retrieved November 11, 2016, from http://www.suasnews.com/2016/04/43057/

UAS Task Force. (2011, March). (United States of America, Department of Defense, Airspace Integration Integrated Product Team). Retrieved November 7, 2016, from http://www.acq.osd.mil/sts/docs/DoD_UAS_Airspace_Integ_Plan_v2_(signed).pdf

ASCI 530 Blog Post 2: Weeding Out a Solution

     A hypothetical UAS has been designed for precision aerial application of fertilizer, however it is overweight. The offending subsystems are Guidance, Navigation, & Control (GNC) and the payload delivery system. In the current state, the vehicle will not be able to meet the advertised performance without using fuel reserves.

Solution

     The first step to solving the problem should be a relatively quick assessment of the GNC and payload systems to find obvious weight penalties associated with the off-the-shelf hardware. This could be as simple as a lighter enclosure for GNC avionics or removing excessive hardware or material from the spray system. Assuming there are no simple solutions, the systems engineer (SE) should take a holistic approach. While GNC and payload may have exceeded their estimated weights, the solution should not necessarily be limited to those areas as they might currently be the most economic designs. Each subsystem team should be directed to identify at least two ways to save weight, the associated cost, and any negative effects. For example, replacing the landing gear wheels with skids may save weight at a low cost, but pass on higher maintenance costs to the user if the skids wear faster than tires. The SE should evaluate the compiled list of ideas and select one or a blend of ideas that incur the least cost to the company while minimally impacting the overall vehicle characteristics.

Table 1. Example of total system cost-benefit analysis for reducing vehicle wight.

     In this example scenario the SE analyzes the benefits of the potential solutions. Removing the battery backups appears to have the best cost-benefit ratio, however a loss of control resulting from an engine-out situation may present unacceptable risk to users or fail to meet certification standards. Similarly, removing heat sinks from computer processor boards may impose constraints in hot weather climates. The SE could also select multiple solutions such as the landing gear skids and thin walled fertilizer tank to meet the design goal.

     For future iterations of this UAS the company should implement three additional practices. First, a requirements-based design process should be used, which will ensure traceability of all configuration choices back to a verified need from the customer (Loewen, 2013). This is directly tied to the second practice of gathering operational data from the current UAS and conducting user surveys. The database can be used to determine requirements for follow-on systems, complete cost-benefit analysis as a function of market demand, and make appropriate sacrifices in the event testing reveals deficiencies. Since the payload versus range problem is critical for the aerial application UAS, the company should also construct a payload-range diagram. This will assist marketing personnel and customers in understanding the capabilities of the vehicle (Ackert, 2013).

Figure 1. Example of a Range-Payload diagram. Reprinted from Aircraft Payload‐Range Analysis for Financiers, by S. Ackert, 2013. Copyright 2013.

     If a range-payload diagram had been drawn for the current UAS design, it might have shown that the performance was acceptable under certain situations (consistent with the marketing campaign) or guided better decision making. For example, if the demonstrated range was found to be between Point B and C in Figure 2, and the results of a market survey yielded few users needed ranges greater than Point B, than perhaps fewer, if any, changes could be made.

Conclusion

     This essay has briefly explored the crisis that ensues when testing reveals serious design deficiencies. A typical cost-benefit example was provided to aid configuration change decisions. Additional recommendations were also provided for future projects.

References

Ackert, S. (2013). Aircraft Payload-Range Analysis for Financiers. Retrieved October 30, 2016, from http://www.aircraftmonitor.com/uploads/1/5/9/9/15993320/aircraft_payload_range_analysis_for_financiers_v2.pdf

Loewen, H. (2013). Requirements-based UAV Design Process Explained. Retrieved October 30, 2016, from https://www.micropilot.com/pdf/requirements-based-uav.pdf

ASCI 530 Blog Post 1: A Short Historical UAS Example

Unmanned aerial systems (UAS) have been in development in the U.S. nearly as long as manned aircraft. A main theme is that the vehicles were intended to replace humans to accomplish missions that are dangerous. The following essay will analyze the Ryan Firebee variants and how they evolved over time.

Ryan Firebee

The Teledyne Ryan Firebee UAS includes a variety of jet-powered vehicles built from 1948 to 1982. The first model production model, the Q-2, was designed as an aerial target for the U.S. Air Force, Army, and Navy who needed to train for emerging jet fighter and cruise missile threats (Parsch, 2003). It could be launched from the air via an A-26 or C-130 host aircraft, or static launched from the ground with an expendable solid rocket motor. At the end of the mission, the vehicle would deploy a parachute and recovery trapeze that could be caught in mid-air by a suitably equipped helicopter, or splash down into water for pickup. By 1963 the Firebee had been redesigned the A/BQM-34 series, which included models that performed from 10 to 60,000 feet up to Mach 0.96 (Tarantola, 2013). Beginning in 1953, a supersonic Firebee II (BQM-34E) was developed to simulate high-speed fighter aircraft for anti-aircraft system testing. The typical Firebee endurance was 90 minutes, but most variants could be equipped with external drop tanks. They could be launched on pre-programmed missions or directly controlled using a line-of-sight link with a range of 300 miles, where operators set goals (ex. 7G level turn) and were provided basic vehicle state data.

Expanding Missions

Realizing that the Firebee line was capable of more, the Air Force began developing a reconnaissance version in 1963. Designated the AQM-34, they completed approximately 34,000 missions over the Vietnam conflict zone with optical sensors or electronic warfare packages (Tarantola, 2013). An advanced signals collection version was also deployed over North Korea from 1970-1973 that provided an unprecedented seven hours of loiter time at 75,000 feet.

Recent History

Although the Firebee production line was closed in 1983, the aircraft were the main target decoy until fielding of the BQM-167 in 2002. These later models featured towed flare decoys for heat-seeking missiles and emitters that simulated the radar signatures of a wide variety of threats (Parsch, 2003). Global Positioning System receivers were also installed to increase navigation accuracy. Of nearly 7,000 Firebees built, the remaining 250 were reserved for research, development, and special activities. In 2003, BGM-34Ls were used during the opening air attacks over Iraq, where they were used to dispense radar-spoofing chaff and employ jamming ahead of manned coalition aircraft (Tarantola, 2013). In 2005, Northrop Grumman was awarded a contract to modify the remaining Firebee systems for advanced decoy and payload dispensing operations (Morris, 2005).

Conclusion

This short essay has analyzed the Ryan Firebee, from its inception as a simple aerial target drone to its role as a modern surveillance and electronic attack platform. While the variants shared generally the same airframe and physical performance, the models developed over 5 decades were significantly improved with state-of-the-art technology. Overall, the systems provided an impressive 83% recovery rate and ensured valuable capabilities were available to the U.S. military. The Firebee system represents a success story in the flexibility and capability of UAS.

References

Tarantola, A. (2013, August 27). The Ryan Firebee: Grandfather to the Modern UAV - Gizmodo. Retrieved October 23, 2016, from http://gizmodo.com/the-ryan-firebee-grandfather-to-the-modern-uav-1155938222

Morris, J. (2005, August 18). Firebee target has first flight with modernized avionics. Retrieved October 23, 2016, from http://search.proquest.com

Parsch, A. (2003). Teledyne Ryan AQM/BQM/MQM-34 Firebee. Retrieved October 23, 2016, from http://www.designation-systems.net/dusrm/m-34.html