(IVAR) - Final Report - Strategic Environmental Research and ...

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adar screen and follow their movements from scan to scan, estimating direction, speed, and their number. These manual radar signal processing methods, while effective in improving bird detection, especially at night when visual methods are highly limited, are time consuming and prone to bias as operators select radar echoes to track. With improvements in digital signal processing, computing, database management and networking technologies, digital avian radars are now commercially available. The modern digital radars have overcome the limitations of their predecessor analog radars through the implementation of detection and tracking algorithms that automatically process bird target echoes to produce bird track data that include the target’s position, heading, and speed estimates versus time on geographically accurate screen backgrounds. An overview of the development of avian radars (both of the analog and digital variety) is provided in Nohara, et al. (2007). Avian radars systems available commercially and employing small, relatively inexpensive X- or S-band marine radars are also described by Herricks and Key (2007). Ruth (2007) provides a summary of the application of avian radar for monitoring birds and the US Geological Survey (USGS) in Fort Collins, Colorado provides on their web site (http://www.fort.usgs.gov/Radar/Bib_Marine.asp) references/links to a number of research papers on this topic. The U.S. Navy, as described in Section 2.4 below, has been a leader in the development of avian radar systems (both analog and digital), and recently the Federal Aviation Administration (FAA) has undertaken the performance assessment of avian radars at civil airports. The Navy has also been responsible for gathering requirements from the user community (see Section 2.3), which has driven the development of new radar features (such as automatic tracking, data streaming, integration and fusion) now available in some commercial, digital avian radars. 2.2 DOD AND FAA AVIAN RADAR DEVELOPMENT The U.S. Air Force and the Federal Aviation Administration developed an avian radar through the Dual Use Science & Technology (DUST) Program (Herricks, et al., 2005). This radar used a millimeter wavelength radar to address ranges to 6 km (3 nmi) and altitudes to 1 km (3000 ft). Although prototypes of this radar were tested at Dallas-Fort Worth Airport (DFW) and the Fermi National Accelerator Laboratory, no commercial development of this avian radar type has occurred. The primary commercial development, and virtually all of the remaining DoD efforts use microwave radar (3 cm and 10 cm wavelengths). The U.S. Air Force (USAF) is using avian radars at several locations that employ a design initially developed by Geo-Marine, Inc. and later modified by DeTect, Inc. This radar system uses horizontally rotating S-band marine radar and one or more vertically spinning X-band radars. Both of these radars are outfitted with an array antenna with a nominal 20° (± 10° from horizontal) coverage. The Defense Department’s Legacy Program Office conducted a competitive selection process and chose Clemson University to develop a near-range avian radar system known as BirdRad (Gauthreaux, 1999). The objective of the BirdRad project was to sample bird populations in the 0-11 km (0-6 nmi), a range that was not adequately covered by other radar systems such as the WSR-88D. A specific goal was to sample at dusk and dawn when birds might be arriving at or departing from military lands on their stopovers during migration. The Legacy Program Office was also aware of the potential dual-use of avian radar systems for both NRM and BASH applications. 10
The original BirdRad system was designed to be an inexpensive, mobile avian radar. It included low-cost commercial off-the-shelf COTS marine radar (Furuno 2155BB) outfitted with a parabolic dish antenna (4º beam width for better altitude resolution) and a desktop PC for displaying and capturing the radar images in graphic files. Five BirdRad systems were built by the Clemson University Radar Ornithology Lab (CUROL) and deployed at three Navy and one Marine Corps air stations, and one Air Force base. Shortly after the first BirdRad units were deployed, the NRM and BASH personnel who were the end-users of these systems - as opposed to radar engineers or ornithologists who developed this technology - began requesting enhancements to these systems. Those requested enhancements included: • Removing the excessive ground clutter that made distinguishing the targets difficult; • Tracking and recording the bird movements automatically; • Remotely controlling and scheduling the radar operation (for example, for dawn and dusk sampling); and • Displaying the bird tracks on facility maps and aerial photographs in ways that would be useful to relate bird activity to known landmarks and the underlying terrain features. In 2002, the Naval Facilities Engineering Command (NAVFAC) tasked the Space and Naval Warfare Systems Center in San Diego, California (SSC-SD 1 ) to undertake a project to investigate whether the requested enhancements to BirdRad were technically feasible and affordable. The SSC-SD team, which included its contractor, Computer Sciences Corporation (CSC), began by conducting an analysis of the requirements of NRM and BASH personnel for collecting bird activity data, with an eye to understanding how radar technology might assist in those efforts. Based on those analyses, researchers at SSC-SD proposed modifying the design of the BirdRad system by replacing the analog signal processor that came with the marine radar with a digital radar processor and sophisticated digital detection and tracking software – capabilities that previously could only be found in expensive military surveillance and tracking radars. The SSD-SD team concluded that recent advances in COTS computing technologies might make these capabilities affordable for avian radar systems. After a competitive procurement, CSC subcontracted with Sicom Systems Ltd. to adapt its MT-Tracker software (now included and branded under the Accipiter® name) to track birds. The resultant enhanced BirdRad, or eBirdRad, system was first deployed in 2004. In 2005, the Federal Aviation Administration Research and Development Program (AAR 411) initiated a comprehensive effort to assess the performance of avian radars and radar support systems that had recently appeared in the marketplace from a few vendors. This effort resulted in the deployment of avian radars in 2006 and the initiation of a comprehensive performance assessment program at civil airports, with the purpose of evaluating radar technologies and the supporting data management and control systems. The University of Illinois Center of Excellence in Airport Technology (CEAT) selected the Accipiter® avian radar systems for initial deployment and assessment. The FAA’s deployment and performance assessment of the Accipiter® AR-1 and AR-2 radars at several civil airports was complementary to the ongoing SSC-SD efforts. As part of that effort, the FAA supported a joint deployment of an Accipiter® AR-1 and an eBirdRad at the Naval Air 1 Now known as the Space and Naval Warfare Systems Center Pacific (SSC Pacific) 11
Page 1 and 2: FINAL REPORT Integration and Valida
Page 3 and 4: Table of Contents List of Tables ..
Page 5 and 6: APPENDIX A. POINTS OF CONTACT .....
Page 7 and 8: Table 6-17. Altitudinal distributio
Page 9 and 10: List of Figures Figure 2-1. Chronol
Page 11 and 12: Figure 6-17. Plot of the northing c
Page 13 and 14: Figure 6-42. eBirdRad display based
Page 15 and 16: Figure 6-82. Hourly track count ove
Page 17 and 18: Figure 6-115: COP display showing f
Page 19 and 20: List of Acronyms Acronym AGL AIP AR
Page 21 and 22: Acronym RST RT SEA SQL SSC Pacific
Page 23 and 24: Carmen Lombardo Naval Air Station,
Page 25 and 26: EXECUTIVE SUMMARY Military bases an
Page 27 and 28: database and redistributed to other
Page 29 and 30: 1 INTRODUCTION 1.1 BACKGROUND Encro
Page 31 and 32: A seventh objective, the Functional
Page 33 and 34: Table 1-1 (cont.). IVAR TASK/ OBJEC
Page 35 and 36: environmental stewardship with miss
Page 37: 2 TECHNOLOGY/METHODOLOGY DESCRIPTIO
Page 41 and 42: 2.4 TECHNOLOGY/METHODOLOGY DEVELOPM
Page 43 and 44: Figure 2-2. Configuration of BirdRa
Page 45 and 46: 2.4.3 eBirdRad - Digital Radars wit
Page 47 and 48: Figure 2-5. Interior view of the eB
Page 49 and 50: accuracy and target continuity over
Page 51 and 52: permanently installed at SEA. Prior
Page 53 and 54: 2.5 ADVANTAGES AND LIMITATIONS OF T
Page 55 and 56: 3 PERFORMANCE OBJECTIVES Table 3-1
Page 57 and 58: Table 3-1 (cont.). Performance Obje
Page 65 and 66: For the third test, Validation Usin
Page 67 and 68: temporal domain by recording all bi
Page 69 and 70: 3.1.2.2.7 Provides Bird Abundance o
Page 71 and 72: difference in the time (i.e., the l
Page 73 and 74: 3.1.6.2.4 Maintenance [SE4.2] We es
Page 75 and 76: Table 4-1. Summary of the IVAR stud
Page 77 and 78: 4.1 MCAS CHERRY POINT Marine Corps
Page 79 and 80: 2006 the primary eBirdRad unit from
Page 81 and 82: (directional WiFi) to the Internet.
Page 83 and 84: • Large (several thousand) flocks
Page 85 and 86: location for demonstrating the capa
Page 87 and 88: 5.1 CONCEPTUAL TEST DESIGN 5 TEST D
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5.3 DESIGN AND LAYOUT OF TECHNOLOGY
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Assuming these lines evidence confi
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that dataset [Section 6.5.1.3]. 5.5
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6 PERFORMANCE ASSESSMENT The Perfor
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ecord the time, Track ID, and other
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Figure 6-1. Percentage of targets c
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Comparing the performance of dish v
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Figure 6-4. The basic sensor elemen
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Figure 6-6. The polygon around the
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Figure 6-8. Diagram of sampling “
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• It takes several scans (nominal
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Session Correla tions 600 500 y = 1
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To evaluate the capabilities of the
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Figure 6-15. Runway 3 at SEA, showi
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comparisons between the RCH-GPS dat
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Figure 6-18. Plot of the northing c
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Figure 6-20. Plot of the easting co
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Conclusion In the quantitative perf
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Table 6-8. Column headings of the T
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Table 6-9 demonstrates quantitative
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Table 6-10. The parameters of targe
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Table 6-11. The position of Visual
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Table 6-12. Solitary targets at MCA
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Figure 6-23. The track of target T2
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intended to demonstrate these syste
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Figure 6-34. Screen capture of bird
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6.1.2 Qualitative Performance Crite
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upper right have completely converg
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Figure 6-38. The progression of the
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The slight difference in alignment
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Figure 6-42. eBirdRad display based
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Figure 6-44. A partial history of t
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6.2 SAMPLING PROTOCOL 6.2.1 Quantit
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Figure 6-46. Image from the track h
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Table 6-14. Dates, times and names
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Figure 6-48. Fifteen-minute (06:04-
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Figure 6-50. Fifteen-minute (02:24-
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We used a TVW to process the plots
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Figure 6-53. In an example of night
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6.2.1.4 Efficiently Stores Bird Tra
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Figure 6-56 shows sites 13-24 in th
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We extracted the radar data for thi
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Figure 6-57. Digital image of the d
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Table 6-17. Altitudinal distributio
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hours apart, showed considerable va
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• The sampling event time period
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underwent a 4-minute initialization
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Figure 6-62. DRP Live application l
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commands we issued to the radar; th
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4. Range Decrease (x7) 5. Range Inc
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Figure 6-65, Figure 6-66, and Figur
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6.2.2.4 Provides Spatial Distributi
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Figure 6-69. A plot of all track ac
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Figure 6-71. Twelve 2-hour historie
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Figure 6-72. TVW application displa
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Conclusion Figure 6-74. Oblique vie
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Archived Data to a GIS We used the
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(SQL). Extracting target data from
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Figure 6-78. Daily, unfiltered, tra
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Figure 6-79. Time periods selected
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Figure 6-82. Hourly track count ove
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esults are displayed in Figure 6-83
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As can be seen in Figure 6-83, the
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Figure 6-84 clearly demonstrates th
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Conclusion We have successfully dem
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LAN within a facility to the operat
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All reference times were recorded i
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Description of Remote Display - As
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mounted laptop computer (Figure 6-8
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very good because the system was sa
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operations personnel or their contr
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Figure 6-90. Alarm status pane and
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Figure 6-92. Alarm triggered as a f
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Figure 6-95. Screen capture of the
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Figure 6-96. An example from a data
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Table 6-29. Differences found betwe
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6.4 DATA INTEGRATION 6.4.1 Quantita
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Figure 6-100. Screen captures for S
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We used a screen-capture program at
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Results Table 6-32 records the time
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We acquired the appropriate plots a
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Figure 6-105. Track histories of ta
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synchronized, both spatially and te
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0.004687 seconds ahead of the NTP t
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Figure 6-108: COP display showing f
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Figure 6-110: TVW display showing t
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The next example from NASWI involve
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Figure 6-114: TVW display showing t
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Figure 6-116: COP display showing a
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Fusion processing was enabled in th
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processing associated with this dat
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Figure 6-122: Track IDs shown for b
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Conclusion We successfully demonstr
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Of course, many other factors contr
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one, Jim Swift, had been exposed to
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Methods The US military 27 designat
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Natural R.esoan:es Br.mch 22541Jolm
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Given these considerations, the IVA
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Results No maintenance was required
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acquired and is testing JRC S-band
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areas of overlap. Data fusion algor
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6.8 FUNCTIONAL REQUIREMENTS AND PER
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Table 7-1. Cost Model for a Standal
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additional processors account of th
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Installation Site Assessment - Rada
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e incurred, depending on what infor
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eal time, avian radars and can dete
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Network Connectivity. The US Depart
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Airport Improvement Program (AIP) f
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9 REFERENCES Anderson, C., and S. O
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APPENDIX A. POINTS OF CONTACT POINT
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POINT OF CONTACT Name Ryan King Mat
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APPENDIX B. ANALYTICAL METHODS SUPP
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METHOD #2: VALIDATION BY IMAGE COMP
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The pattern of yellows and blues in
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Radar Team (RT) Site Selection Sinc
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will measured the magnetic bearing
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Figure B-6. Using a GPS to record s
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• Visual Observer - observes bird
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Figure B-9. Flowchart of target con
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VT: “Radar, Team 2-Alpha copies T
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eam and the VTs have difficulty loc
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why it was changed, who made the ch
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METHOD #4: CONFIRMATION OF BIRD TAR
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Figure B-12. Duplexed image showing
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Table B-2. Dates, times, and antenn
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For the analysis of the simultaneou
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Table B-3. Altitude of the radar be
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Figure B-17. Diagram of sampling
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METHOD #6: DEMONSTRATING REAL-TIME
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APPENDIX C. DATA QUALITY ASSURANCE/
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APPENDIX D. SUPPORTING DATA D.1 Par
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Table D-1 (cont.). Date Track ID Up
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D.2 Listing of One-Hour Track Histo
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Table D-2 (cont.). 07:00-08:00 WI_A
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APPENDIX E. SURVEY OF AIRPORT PERSO
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used as the real-time target becaus
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Table E-1. Remote radar display lat
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7. Please rate the following where
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