Module 7.4 – UNSY 605

In order for unmanned systems to become a more viable option for many applications, the sense and avoid technology they operate must improve significantly.  The currently available options for unmanned systems do not provide effective enough detection and response capabilities to be viable options.  As a result, unmanned aerial vehicles (UAVs) present a severe risk for mid-air collisions with other aircrafts or stationary objects such as buildings.  Due to the risk of collision associated with flying UAVs, they must be flown within line of sight, which restricts their use for many applications at this time (Roden 2016).  The development of sense and avoid technology is advancing in two stages:  improved sense and avoid technology for better information relay to an operator and the development of completely autonomous sense and avoid technology (Roden 2016).  Both of these stages of development face major challenges, but there are some sensors available for operator-controlled UAVs.

            One popular avenue of improving sense and avoid sensor for UAVs has been to incorporate information from Automatic Dependent Surveillance-Broadcast (ADS-B) transponders.  There are two parts to an ADS-B, the ADS-B In and the ADS-B Out (Cincinnati Avionics 2016).  The ADS-B Out uses onboard GPS to transmit its position information to Air Traffic Control (ATC) while the ADS-B In receives position information on other aircraft carrying an ADS-B transponder (Cincinnati Avionics 2016).  uAvionix has designed several versions of their ADS-B transponders for commercial usage and the ping2020 ADS-B transceiver is perfect for use on small UAVs.  The ping2020 weighs only 20 grams and has a minimal power requirement at 500 mW (uAvionix 2016).  Aside from its small size, the ping2020 is optimal because it accomplishes both the ADS-B In and ADS-B Out functions (uAvionix 2016).  The ping2020 can detect objects within a 100 mile radius on two ADS-B In frequencies, 1090 MHz and 978 MHz (uAvionix 2016).  As for the ADS-B Out, the ping2020 transmits on the 978 MHz frequency (uAvionix 2016).  The only detail about the ping2020 is not ideal is the price.  Though I could not find a valid source for the price, I found one listing of the ping2020 for $1200, which is higher than desired when it comes to such a small component. 

            The ping2020 is a solid starting point for the first stage of sense and avoid technology development, but it is by no means a final solution.  The idea behind implementing an ADS-B transponder into a sense and avoid sensor is helpful, but it has its major faults.  The main issue is that in order to sense another aircraft that aircraft also has to be equipped with an ADS-B transponder.  The Federal Aviation Association (FAA) recently mandated that operate in U.S. National Airspace must be equipped with ADS-B by the year 2020, which means that the number of aircraft which are detectable by the ping2020 will be much higher (uAvionix 2016).  However, the ADS-B makes no improvements on the sense and avoid capabilities of stationary objects such as buildings or trees.  More than likely, small UAVs will not be operating in a high altitude environment for extended periods of time, which means that they will have to navigate obstacles presented by lower altitude areas.

            The bottom line for commercial small UAV operations in the future is that the discrimination capabilities of sense and avoid sensors must improve drastically.  Adding additional components, such as the ping2020 ADS-B, can help patch some of the issues for a short time.  But in the end, the sense and avoid sensors themselves have to become more effective to move forward in both operator-controller and autonomous UAV operations.

References

Cincinnati Avionics.  (2016). ADS-B 101:  what you need to know. Retrieved from http://cincinnatiavionics.com/ads-b-101-what-you-need-to-know/

Roden, M.  (2016). SkyTech Event:  UAV Conference & Exhibition. Retrieved from http://www.skytechevent.com/#!Sense-and-Avoid-The-Technology-to-Watch/c1leh/559bb52c0cf2361ae7868374

uAvionix.  (2016). PING-2020 ADS-B Transceiver.  Retrieved from http://www.uavionix.com/products/ping2020/

Module 6.4 – UNSY 605

The use and development of unmanned systems in the maritime environment has moved slowly when compared to its counterparts on the ground and in the air.  Typically, these maritime systems fall into two categories, autonomous underwater vehicles (AUVs) and unmanned surface vehicles (USVs).  In particular, AUVs face a number of challenges in their operational domain that have slowed their progress and widespread implementation.  However, Bluefin Robotics seems to be on the leading edge with AUV technology as their Bluefin-21, which has been purchased by the U.S. Navy, was inserted into search and rescue efforts for the Malaysia Airlines Flight 370 (Makinen 2014).  One of the main reasons that the Bluefin-21 was selected for use by the U.S. Navy are the capabilities and technology provided by the control station and its software.

Bluefin Robotics produces the Bluefin-9, -12S, -12D, -21, and HAUV AUVs all of which operate on the same Operator Tool Suite software package (General Dynamics 2016).  The software provides a Windows-based user interface which allows the operator to monitor and manage all aspects of the system and its mission (General Dynamics 2016).  There are three main functional modes provided by the Operator Tool Suite: Mission Planner, Dashboard, and Lantern.  As its name suggests, the Mission Planner tool allows for planning and verification of missions ranging from basic to complex plans (General Dynamics 2016).  The Dashboard tool provides an interface for vehicle testing and mission monitoring on a chart-based, operator-specified display (General Dynamics 2016).  Finally, the Lantern tool is used for post-mission sensor data display, analysis, and reporting (General Dynamics 2016).   

Since all of the systems produced by Bluefin Robotics are autonomous, there is not a great need for operator feedback within the system.  However, the system could be greatly improve if the technologies available in the Lantern tool were implemented in a real-time fashion.  Even though there is not an “operator” for an AUV, there is someone monitoring the progress of the system.  In the current system setup, the system monitor can only observe the status of the system components and track the progress of the system along its mission course.  Upgrading the Operator Tool Suite software to allow for real-time or near real-time sensor data display would provide great benefits for its mission accomplishment.  Having the capability to monitor sensor data immediately would allow for the system operator to determine if changes to the planned mission are needed. 

An example of when this ability would be beneficial is a search and rescue scenario similar to that of the Malaysia Airline Flight 370.  On the current system, the operator would have to wait until a search mission has been accomplished to determine if anything of worth was discovered.  If in the post-mission analysis, a significant discovery was made, the operator would then have to plan an entirely new mission to re-examine the area of interest.  Conversely, a system with the real-time sensor data display would provide the capability for the operator to make that same determination on the spot and adjust the current mission plan accordingly.  Creating a new Operator Tool Suite with this ability would increase the efficiency of search and rescue efforts significantly, reducing the burdens of time and cost.

Improving the Operator Tool Suite would certainly address an area of need in terms of conquering the hardships of AUV operations.  However, there are many other tasks that have to be tackled before the use of unmanned systems in the underwater domain becomes as pronounced as in the air and on the ground.  But each problem that is solved will make the successive progress a little easier.

References

General Dynamics.  (2016). Operator Software.  Bluefin Robotics.  Retrieved from http://www.bluefinrobotics.com/technology/operator-software/

Makinen, J.  (2014). Malaysia Airlines plane search goes underwater.  Los Angeles Times.  Retrieved from http://articles.latimes.com/2014/apr/14/world/la-fg-malaysia-bluefin-20140415

Module 4.5 – UNSY 605

            The RQ-21A Blackjack is a small, tactical unmanned aerial vehicle (UAV) which has been designed to replace the Boeing Scan Eagle in U.S. Navy intelligence, surveillance, and reconnaissance (ISR) operations (MilitaryFactory 2016).  The Blackjack is capable of both deck-launch and land-launch operations for the Navy and Marines due to the “SuperWedge” catapult launching system (MilitaryFactory 2016).  The system is a fixed-wing aircraft which measures over 8 feet in length and has a 16 foot wingspan (Insitu 2015).  An important piece of any ISR aircraft being able to complete its mission is the data processing and handling portion of the system.  The Blackjack uses a combination of three information software packages to handle the data collected by the sensors:  TacitView, Catalina, and Tungsten (Insitu 2016). 

The Tacitview and Tungsten software can be used by the operator for the exploitation of images and data collected by the Blackjack (Insitu 2016).  The Catalina software package is the portion that deals with the majority of the processing, storage, and dissemination of the collected data (Insitu 2016).  Catalina can index media and metadata and subsequently extract and edit information contained within these indexed files (Insitu 2015).  In addition to processing, Catalina provides for the dissemination of media and metadata as either files or streams to several nodes simultaneously (Insitu 2015).  The Catalina ensures that the dissemination of information is secured using Transport Layer Security (TLS) and Secure Sockets Layer (SSL) security protocols and methods (Insitu 2015).  Finally, Catalina has the ability to work across multiple platforms for users such as Linux or Windows due to its C++ construction (Insitu 2015).   The combination of data processing software provided on the Blackjack allow for effective and secure collection, dissemination, and exploitation of ISR products. 

The Blackjack has multiple sensors which are responsible for providing data to the trio of processing software.  It is equipped with an electro-optic imager, a mid-wave infrared imager, a laser rangefinder, and an IR marker (Insitu 2015).  With these sensors, the Blackjack can collect multiple ranges of ISR information for up to 16 hours per mission with a power requiremtn of 350 W (Insitu 2015).  The sensor suite has a Transmission Control Protocol/Internet Protocol (TCP/IP) Ethernet connection to the information processing software (Insitu 2015).  The TCP/IP is a four-layered secure protocol which accomplishes packaging, encryption, and transmission of collected data within the system (Microsoft 2016).  These components work together to accomplish the ISR missions required by the Navy and Marines.    

The Blackjack system is effective in accomplishing its assigned ISR missions, but there are ways that it can still be improved.  When the Navy or Marines order a Blackjack package, the package includes five air vehicles and two ground stations (MilitaryFactory 2016).  So the information processing software will be working with data from five separate Blackjack UAVs.  The amount of data being collected and sent to the processing software could be quite large if multiple aircraft are active at a time.  My suggestion would be that the Blackjack implement some form of compression treatment to the data in order to allow the processing equipment to more easily handle information from multiple sources.  The smaller files or streams would allow for quicker sorting and dissemination to the separate ground stations and users.

References

Insitu.  (2016). Information Processing Software.  Retrieved from https://insitu.com/information-delivery/information-processing

Insitu.  (2015). Catalina.  Key Features and Capabilities.  Retrieved from https://insitu.com/information-delivery/information-processing/catalina

Insitu.  (2015). RQ-21A Blackjack.  Product Card.  Retrieved from https://insitu.com/information-delivery/unmanned-systems/rq21a

Microsoft.  (2016). TCP/IP Protocol Architecture.  Retrieved from https://technet.microsoft.com/en-us/library/cc958821.aspx

MilitaryFactory.  (2016). Boeing Insitu RQ-21 Blackjack (Integrator) Unmanned Aerial Vehicle (UAV) (2014).  Retrieved from http://www.militaryfactory.com/aircraft/detail.asp?aircraft_id=1045

Module 3.4 – UNSY 605

There are a vast array of choices to make when developing an unmanned aerial vehicle (UAV), all of which will have an important impact on the success of the system.  There are many choices that come to the forefront when discussing their impact, such as the power source, the type of engine, and the type of sensor implemented by the UAV.  But one aspect of designing a UAV that has underrated importance to the performance of the system is the placement of sensors on the system.  When systems are being designed, sensor placement decisions should be made based on the application a UAV is intended to accomplish.  In order to demonstrate this principle, I will examine the design structure and sensor placement formats for two different UAV applications:  aerial photography and UAV racing.

One of the most popular uses for commercial UAVs is aerial photography as both a business opportunity and as a hobby.  The business applications of aerial photography include cartography, real estate advertisement, and environmental studies among others.  But as earlier stated, the use of UAVs for aerial photography is also a hobby for many who just enjoy the artistic medium of photography.  There are many versions of UAVs that can accomplish aerial photography for business and pleasure, but I will be evaluating the Yuneec Typhoon Q500 quad-rotor for this examination.  The Typhoon is designed for flight under 400 feet altitude for approximately 30 minutes at a time (Yuneec 2016).  In order to collect aerial images, the Typhoon carries a CGO3 gimbal camera which is capable of high definition still and video photography (Yuneec). 

As you can see in Figure 1 below, the CGO3 is mounted underneath the frame of the Typhoon.  The placement of the camera underneath the frame of the UAV is optimal for aerial photography for several reasons.  First, it ensures that the images will not be impeded by the body of the UAV regardless of the angle or orientation in which the camera is pointing within its 115° Field of View (FOV).  This is important for the quality of the photos, but it is also important as it ensures the operator has a clear view with which to navigate the Typhoon.  In addition to being under the frame of the multi-copter, the camera is also mounted near the front end of the Typhoon.  It is significant that the camera is near the front of the frame again for navigational purposes so that the operator has a clear view of wherever the Typhoon is pointed.

 

A growing hobby area within the use of UAVs is First Person View (FPV) racing.  For you Star Wars buffs out there, FPV racing with a UAV is currently about as close as you can get to pod-racing.  As evidence of its growing popularity, there was a FPV Drone Nationals held in Sacramento, California last year (Kapper 2015).  To study the sensor placement for this UAV application, I will be looking at the Immersion RC Vortex 250 Pro.  The Vortex is a small quad-rotor UAV weighting only about 1 pound depending on the configuration (ImmersionRC Ltd 2016).  The Vortex uses a FatShark 700TVL camera for real-time video streaming to the racer (ImmersionRC Ltd 2016).  As shown in Figure 2, the Vortex’s camera is located within the “nose” of the UAV frame.  Unlike the Typhoon, whose main purpose is to look down, the main focus of the Vortex is what is ahead of the UAV.  The pilot needs to have a clear focus of the course in front of the Vortex, making the placement ideal. 

 

There a many important considerations to examine when designing a UAV for any application.  Sensor placement is one consideration that may go unnoticed, but as shown in the Typhoon and the Vortex, sensor placement is essential for the effective use of any UAV. 

References

ImmersionRC Ltd.  (2016). Vortex 250 Pro.  Retrieved from http://www.immersionrc.com/fpv-products/vortex-250-pro/

Kapper, C.  (2015). Five Essential Tips for Beginning Pilots.  PC World.  Retrieved from http://www.pcworld.com/article/2997557/consumer-electronics/first-person-view-drone-racing-five-essential-tips-for-beginning-pilots.html

Yuneec.  (2016). Typhoon Specifications.  Typhoon Q500.  Retrieved from http://www.yuneec.com/Typhoon-Specifications-Typhoon-4K