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OBSERVATIONAL VALIDATION OF AVIAN RADAR SYSTEMS

Wendell Bunch Edwin Herricks, PhD. OBSERVATIONAL VALIDATION OF AVIAN RADAR SYSTEMS. Introduction. Existing airport surveillance radars Designed for air and ground traffic control Not readily adaptable for wildlife purposes Avian radar systems

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OBSERVATIONAL VALIDATION OF AVIAN RADAR SYSTEMS

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  1. Wendell Bunch Edwin Herricks, PhD OBSERVATIONAL VALIDATION OF AVIAN RADAR SYSTEMS

  2. Introduction • Existing airport surveillance radars • Designed for air and ground traffic control • Not readily adaptable for wildlife purposes • Avian radar systems • Digital processing added to COTS marine radar and optimized for bird detection • X-band and S-band • New technology w/few users and no airport experience

  3. CEAT Performance Assessment • Multiple year program assessing avian radar systems at civil airports • Initial efforts intended to understand radar physics/system abilities • A critical issue is validation of capabilities of avian target detection and tracking • Visual observation of birds

  4. CEAT Validation Efforts • Address ground-truth issues • Validate in airport settings • Use target rich environment of Whidbey Island to conduct long term observations • Coordinate with IVAR efforts • Evaluate methods

  5. Issues identified in ground-truth efforts and • validation studies • observers challenge radar detection • radars challenge observers and methods • visualizing the beam coverage (height and • width) • locating specific targets • judging distance and altitude

  6. Location: NAS Whidbey Island WA

  7. Primary sensor X-band radar 3cm wave length

  8. Method of visual observation • 30X spotting scope aligned to true north • radar computer and watch synced ± 1 sec • data collected in high and low clutter areas • viewing angles separated by 20 degrees • two view samples at each angle, high/low • 20 second sample periods • data collected: date/time, family or specie, number of birds, general direction of travel, bearing target observed • time stamp when target on vertical center of spotting scope

  9. Findings • Detection Issues: • Aspect/RCS • Aspect -relation of the target to radar beam • RCS - effective target area, changes with aspect • RCS must exceed level of clutter

  10. Clutter: Ground and Sea • Undesirable radar returns • Sea clutter – tracks short high speed • Wind speed/direction determined effect

  11. Ground and Sea Clutter

  12. Effects of sea clutter on tracking

  13. Detection Issues: cont. • Position Relative to Clutter • gulls: >20, <20, <5 • Large sea ducks: CEAT and IVAR • RCS? • Flight Behavior • constant heading = consistent tracking • un-predictable flight challenges all radar • shadowing in flocks • Duration of Flight • must be long enough

  14. Detection Issues: cont. • Weather • rain/snow hinders detection and tracking • can generate large numbers of detections and tracks • tracks of short duration with speeds similar to birds

  15. Observation Issues • weather conditions hindered use of spotting scope in strong winds/rain • range to targets difficult to estimate • limited to daylight hours

  16. Validation Methods • Requirements to validate target time, direction of travel, bearing, within beam dimensions for the bearing • archived radar data replayed • two examples

  17. Surf scoter - 305

  18. Bonaparte’s Gull - 601

  19. Conclusions • Avian radar capable of tracking bird sized targets • Researchers have shown radar can track movement over larger areas than visual observations • Research needed: potential to monitor bird activities while evaluating limitations of location and radar physics • NAS Whidbey research has shown limitations with the current technology

  20. Conclusion cont. • Factors Compromising Detection • target aspect • target size • flight behavior • target position relative to clutter • overall clutter environment • weather

  21. Conclusions cont. • Use of Avian Radar Systems • careful evaluation of clutter levels to ensure tracking in desired area • will require some level of validation • more complex environments = more validation

  22. QUESTIONS?

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