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Technologies for Integration of Small Unmanned Aircraft Systems (S-UAS) in National Airspace System Matthew Dechering Manish Kumar Contents

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Technologies for Integration of Small Unmanned Aircraft Systems (S-UAS) in National Airspace System Matthew Dechering Manish Kumar Contents Technologies for Integration of small Unmanned Aircraft Systems (s-UAS) in National Airspace System Matthew Dechering Manish Kumar Contents 1. Introduction 2. Technology Survey 3. Existing Solutions 4. Operational Requirements for Urban Air Mobility 5. Solutions for Urban Air Mobility 6. Ongoing/Future Work 7. Conclusions Introduction: Small Unmanned Aircraft Systems (s-UAS) • s-UAS have generated a lot of interest in civilian domains: – Emergency Management, Law Enforcement, Infrastructure Inspection, Package Delivery, Imaging/surveillance • The FAA expects between 162% and 432% growth in number of unmanned flights by 2021 • Low end estimate of 2.75 Million units in the air by 2021, up from 1.10 million units Concept – The UTM Problem • A futuristic notional scenario of UAS usage in National Airspace System consists of a large number of UAS operating in crowded airspace – Safety and reliability issues in autonomous operations – Beyond Visual Line of Sight (BVLOS) operations risky • Objectives of UTM: maintain safe separation with other manned/ unmanned aircraft to avoid collisions while fulfilling UAS mission • Challenges: involves integration and development in several technological areas: – Computation – algorithms for collision-free path planning, tracking of UAS – Sensing - onboard and off-board to obtain situational picture of environment Source: FAA drone vision- http://www.airtrafficmanagement.net/ – Communication – enable information sharing 4 Concept – UTM Requirements • Mission planning – Allows users to request, specify and modify missions of multiple UAS – Keeps track of all UAS in the airspace User interface / front end for mission – Obtain collision-free and optimized flight planning path planning considering all UAS in the airspace • Detect-and-Avoid (DAA) – Have the ability to detect and track other UAS and structure in the airspace Path planning in an urban airspace – Onboard/ground-based sensors or ADS-B – Ability to modify the flight of UAS to avoid the collision in a local manner Detect and Avoid (DAA) - https://vigilantaerospace.com 5 Study Goals • Study advances, identify potential issues, and propose new solutions • Focus on Sense and Avoid (SAA) and Unmanned Aircraft Systems Traffic Management (UTM) aspects of s-UAS integration in National Airspace System Specific Aims of the Project • Specific Aim # 1: Survey of Existing and Emerging Technologies to determine near-term capabilities • Specific Aim # 2: Comparative study of existing solutions proposed by industry, academia, and government • Specific Aim # 3: Development of operational requirements for UTM • Specific Aim # 4: Solutions for these operational requirements Specific Aim # 1: Technology Survey • Sensing Devices • Onboard Computing • ADS-B and GPS • Communication Specific Aim # 1: Sensing Devices-LIDAR Product Price Type Weight (g) Range (m) Power (W) Hokuyo 3D-LIDAR YVT-X002 $4,825 3D Scan 750 50 8.4 Hokuyo UST-10LX $1,700 Planar Scan 130 30 3.6 • LIDAR is commonly used for its Hokuyo UTM-30LX $4,800 Planar Scan 210 30 8.4 Hokuyo UTM-30LX-EW $5,290 Planar Scan 210 30 8.4 low cost and low SWAP (Size, Hokuyo UTM-30LX-F $5,000 Planar Scan 210 30 8.4 Hokuyo UXM-30LX-EW $5,165 Planar Scan 800 30 7.2 Hokuyo UXM-30LXH-EWA $5,875 Planar Scan 1200 80 7.2 Weight, and Power) compared to Ibeo LUX $20,000 Planar Scan 900 200 10 Ibeo LUX 8L $28,899 Planar Scan 1000 200 10 other sensing technologies. Ibeo LUX HD $21,599 Planar Scan 1000 120 10 Ibeo miniLUX $20,000 Planar Scan 450 40 7 lightware SF40/C $999 Planar Scan 229 100 4.5 • More expensive 3D scanning Quanergy M8 $1,000 3D Scan 800 150 15 Quanergy M8-1 $6,100 3D Scan 900 200 18 Quanergy S3 $250 3D Scan Unknown 150 Unknown LIDAR has shown success in Quanergy S3-Qi $1,200 3D Scan Unknown 150 Unknown RIEGL VQ-480-U Unknown Planar Scan 7500 950 55 autonomous vehicles on the ground RIEGL VUX-1UAV Unknown Planar Scan 3750 920 60 Scanse Sweep $349 Planar Scan 120 40 3.25 and in the air. Spectrolab SpectroScan 3D Unknown 3D Scan 2018 20 30 Velodyne HDL-32E $25,000 3D Scan 2000 100 12 Velodyne Puck Hi-res $8,000 3D Scan 830 100 8 Velodyne Puck LITE $8,000 3D Scan 590 100 8 Velodyne PUCK VLP-16 $8,000 3D Scan 830 100 8 Specific Aim # 1: Sensing Devices-RADAR • Typically more expensive Update Name Supplier Range Accuracy Weight Dimensions Power rate FOV 11.4 x 8.7 x DK-sR-1200e lmst 307 m 0.6 m 280 g 4.25 cm 4.5 W 10-200Hz 65 x 24 ° and higher SWAP than its 7.6 x 5.4 x 1.3 muSharp Aerotenna 120 m 0.22 m 43 g cm 1.25 W 90 Hz 50 x 30 ° 18.7 x 12.1 x 4 120 x 80 LIDAR counterparts MESA-DAA Echodyne 750 m 3.25 m 817 g cm 35 W 1 Hz ° 20.3 x 16.3 x 4 120 x 80 MESA SSR Echodyne 750 m 3.25 m 1250 g cm 45 W 2 Hz ° integrated 13 x 10 x 17.5 • Still a new area the IRIS Sensor robotics 66 m 1.24 m 360 g cm 4.5 W 3.4 Hz 90 ° 12.7 x 20.32 x 120 ° x DAA-R20 Fortem 1500 m 0.0508 m 464 g 2 cm <60 W 8 Hz 40 ° companies are exploring 11.5 x 11.5 x muSharp 360 Aerotenna 40 m 0.22 m 243 g 6.7 cm 2.5 W 80 Hz 360 ° Specific Aim # 1: Sensing Devices-Cameras Name Supplier resolution and frame rate power SENSOR FLIR DUO Dual Sensor Uncooled VOx FLIR Systems 1920 X1080 2.2 W 5-26 VDC Thermal Camera Microbolometer, • The most Diverse group of DJI Zenmuse X5S DJI 20.8 MP CMOS 4/3" Raspberry Pi Camera 3280 x 2464 3.7V DC Sony CCD Edmund 56-578 edmund 768 x 492 12V DC @ 130 mA Interlaced CCD sensors by far HackHd 1080p -- 4000 x 2250 3.7V DC @ 500 mA Interlaced CCD PointGrey BlackFly model Point Grey 1280 x 1024 @ 60 FPS 5V / 380mA BFLY-U3-20S4C-CS PointGrey Flea3 model FL3- Point Grey 1624 x 1224 @ 15 FPS 5V / 380mA • Conventional Cameras need U3-13E4C-C e-con Systems' 4224 x 3156 @ 18 FPS, 1280 x 1080 @ E-con 5V / 380mA CMOS Image See3CAM_CU130 45 FPS binocular vision to sense e-con Systems' E-con 1920 x 1080 @ 42 FPS 5V / 380mA CMOS Image See3CAM_CU30 IDS uEye cameras UI- IDS (1280x1024, 60fps, 8bit mono) 5V / 380mA CMOS Image distance. 3241LE PointGrey Blackfly GigE PoE Power over Ethernet color camera with CS-mount Point Grey (1280x1024, 60fps, 8bit mono) (PoE); or 12 V CMOS Image • Stronger in bright conditions, lens and Global Shutter nominal (5 - 16 V) LI-USB30-IMX185 2.42M 2.42M pixels CMOS Resolution: 1952H x 1241V USB 3.0 Camera Sensor where radar and lidar can 1080p/29.97 mode to 720p/59.94, FCBEH3300 Sony 1,450,000 pixel 20x Zoom HD Color CMOS Image Block Camera, image stabilization struggle Color Camera Module Sony 6 to 12 V DC/ 3.0 W CCD FCB-EX1020/EX1020P LI-M034USB3-AF 720p WDR USB 3.0 Camera with 18x Aptina MT9M034 1.2M pixels Sensor USB 3.0 +5VDC Zoom Lens Hero4 Session goPro 1440p30 1080p60 720p100 480p120 Hero4 Silver goPro 4k15 2.7k30 1080p60 720p120 480p240 Specific Aim #1: Computing Devices Open Waypoint ADS-B Board Company Source Navigation Compatibility A2 DJI No Yes Yes AeroQuad v2.2 Kit AeroQuad Yes Optional AfroFlight Naze32 Rev6 Acro HobbyKing APM 2.8 3DR Yes Yes Yes • There are a large amount of AutoQuad v6.6 Viacopter/FlyDuino Yes Yes Crius All In One PRO Crius/Hobbyking Yes Optional Crius MultiWii Lite Crius/Hobbyking Yes Crius MultiWii SE Crius/Hobbyking Yes Optional autopilots that can boast high DJI Naza-M V2 DJI No Yes Yes DJI Wookong DJI No Yes Yes Erle Brain 3 erlerobotics Yes Yes Yes Erle-Brain PRO erlerobotics Yes Yes Yes FF Auto Balance Controller Free Flight No accuracy with a proper GPS FY-40A Feiyu Tech No FY-41AP Feiyu Tech Optional FY-41AP Lite Feiyu Tech FY-DOS Feiyu Tech connection HobbyKing KK2.1HC HobbyKing Yes HoverflyPRO Hoverfly Optional iNav Sirius™ AIR3 F3 SPI MultiWiiCopter Yes Add-on Intel Aero Intel Yes Yes Yes • Some are capable of intelligently LibrePilot CopterControl/Atom LibrePilot Yes Platform LibrePilot Revolution LibrePilot Yes MikroKopter Flight-Ctrl ME 2.1 MiKroKopter Yes avoiding obstacles at low altitude Complete Navio2 emlid Yes Yes Yes Naza-M Lite DJI No Optional Yes Panda2 Feiyu Tech Yes • ADS-B connectivity is common Pixfalcon holybro Yes Yes Yes Pixhawk 2.1 Cube proficnc Yes Yes Yes Pixhawk Mini 3DR Yes Yes Yes Pixracer R14 mRobotics Yes Yes Yes but not ubiquitous RVOSD 6 Range Video Yes SmartAP 3.0 Pro SmartAP Yes SmartAP 4 Set SmartAP Yes Yes Snapdragon Flight Autopilot Intrinsyc Yes Yes Yes UAVX-ARM32 Full Sensors QuadroUFO Yes Specific Aim #1: ADS-B and GPS Input ADS-B ADS-B Internal • Low SWAP ADS-B and GPS have a few Product Refernce Power (W) Weight (g) in out Size (mm) GPS products on the market ping2020 uAvionix 0.5 20 yes yes 25 x 39 x 12 on ping2020i ping1090 uAvionix 0.5 20 yes yes 25 x 39 x 12 on ping1090i • GPS accuracy is limited to 7.8 m unless XPS-TR Sagetech 100 no yes 89 x 46 x 18 no additional technology is used to improve XPG-TR Sagetech 100 no yes 89 x 46 x 18 yes the results MXS Sagetech 15 150 yes yes 84 x 64 x 19 available • GPS denial and multipath errors limit the usage of GPS in urban “canyons” created by buildings • ADS-B is not a large range of broadcast frequencies.
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