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

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• Data Streaming – store the numerical data generated for each tracked target locally and stream them reliably over a network to real-time or historical applications. • Data Integration – Combine tracks from independent radars without overlapping coverages into a common operational picture (COP) that increases situational awareness. • Data Fusion – Fuse duplicate tracks from independent radars with overlapping coverages in real time into common tracks to increase situational awareness and track continuity. The demonstration study sites for the IVAR project included: Marine Corps Air Station Cherry Point, NC; Naval Air Station Patuxent River, MD; Naval Air Station Whidbey Island, WA; Elmendorf Air Force Base, AK; Sea-Tac International Airport, WA; Edisto Island, SC; and Accipiter Radar Technologies, Inc., Ontario, Canada. We developed 31 Performance Metrics to evaluate the five Task Objectives listed above. One Metric, “Tracks Single Birds and Flocks”, was divided into three related metrics, and we added a sixth Task Objective “Additional” with five additional metrics. Of the resultant 38 Performance Metrics, 24 were quantitative and the other 14 were qualitative. All 38 Performance Criteria were met or exceeded. The results of those demonstrations are summarized below. Automatic Tracking. First we demonstrated that the radar processor could track synthetic, software-generated targets with known, complex target dynamics. Next, two-person teams of observers visually confirmed as birds more than 1500 targets tracked by the digital avian radars during fall and spring campaigns at four different geographic locations; we employed a thermal imager to confirm targets tracked by eBirdRad at night were birds. We also tracked a remote-controlled helicopter with the radar to check the accuracy of the spatial coordinates the radar processor generates for each target. Finally, we demonstrated the radar could track birds at ranges beyond the perimeter of a very large military airfield, could readily track more than 100 targets simultaneously, and could record in real time a host of parameters for each tracked target. Sampling Protocols. To illustrate the breadth and depth of the radar’s ability to track targets in realistic operational settings, we demonstrated these systems can track targets continuously, 24/7 for years, through a complete 360° field-of-view, out to a range of at least 11 km (6 nautical miles), and up to an altitude of ~1 km (3000 feet) – the nominal bounds for short-range avian radar systems. We further demonstrated the sampling schedules of these systems can be pre-set or remotely controlled for unattended operations, and that they can detect 50 times more birds than human observers using conventional visual methods. Finally, we demonstrated that the volume of data generated by these systems over these time periods fits onto COTS mass storage devices and can be displayed on maps or graphs to show bird activity patterns in time and space. Data Streaming. To demonstrate that the detections (plots) and tracks data generated by the radar can be transmitted across local- or wide-area communications networks to where they are needed, we transmitted data generated by an avian radar in Seattle more than 3000 km across the Internet to the ARTI Headquarters in Ontario with no data loss and 100% network uptime. We further demonstrated that these data could be organized into a xxvi
database and redistributed to other workstations and applications in real time. We also demonstrated users can configure the radar processor to generate automatic alerts that are transmitted over a variety of media to notify personnel that a predefined event has occurred (e.g., too many birds entering a delineated airspace). Finally, we demonstrated streaming live radar data to personnel in the field to alert them to bird activity as it occurs. Data Integration and Data Fusion. Data integration and data fusion combine the plots and tracks being streamed from two or more independent radars to expand coverage, increase situational awareness, and extend track continuity. We demonstrated data integration, which displays the tracks from radars with or without overlapping beams in a single common operational picture (COP), by merging tracks from widely-separated radars and showed the time latencies between the two systems were minimal. For data fusion, which combines into common tracks the individual tracks of a target from multiple radars in their area(s) of overlap, we showed that pairs of radars could be synchronized both temporally and spatially, and that the processing time needed to fuse tracks was small – in some cases, 30-times faster than real time. Additional. We also demonstrated that the cost of operating an avian radar is low relative to the other methods of providing the same spatial and temporal coverage; that the reliability of these systems is high; and that they are already proving their worth in military and civil applications. Cost Analysis. The cost of acquiring, installing, and operating an avian radar system can vary greatly depending upon the facility’s requirements. Based on a 5-year life-cycle, the cumulative cost for a single, integrated, trailer-mounted system that would be optimal for most military facilities is approximately $450K. An integrated system would provide remote control and remote access for visualizing and analyzing the target track data, and could reduce costs through remote maintenance by the vendor. Other costs would include installation (concrete pad and utilities) and operation and maintenance costs on the order of 10% of the purchase price. Technology Transfer. The following resources are available to transition avian radar system technology to operational use at military facilities: • Commercial equivalents of all the products evaluated by the IVAR project are available for purchase or lease and vendor web sites are provide in this Report. • The Functional Requirements and Performance Specifications for Avian Radar Systems addendum to this Report was developed from the IVAR studies. • FAA Advisory Circular 150/5220-25 (FAA, 2010) provides guidance and performance specifications for selecting, deploying and operating avian radar systems at civil airports. Much of the FAA guidance and specifications are equally applicable to military airfields; many of the performance specifications are identical to those developed by IVAR. • Personnel from the Navy, Marine Corps, and Air Force facilities that participated in the IVAR project are available to assist in understanding how avian radar technology might meet the requirements of natural resources management and BASH applications. • The Air Force has, and the Navy is finalizing, a BASH Program of Record that provides both the policy and funding guidelines for avian radar systems technology. xxvii
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: EXECUTIVE SUMMARY Military bases an
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 and 38: 2 TECHNOLOGY/METHODOLOGY DESCRIPTIO
Page 39 and 40: The original BirdRad system was des
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
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4.1 MCAS CHERRY POINT Marine Corps
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2006 the primary eBirdRad unit from
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(directional WiFi) to the Internet.
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• Large (several thousand) flocks
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location for demonstrating the capa
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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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