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

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3.1.1.2.1 Automates Real-Time Tracking of Radar Echoes [PA1.2] Digital avian radars are relatively new technology and few of the potential end-users will have had any practical experience with this technology. We designed this qualitative criterion to examine two fundamental questions about the capabilities of the Accipiter® digital radar processor (DRP) use in the IVAR (and CEAT) studies. First, how well can the DRP track targets with well-defined flight dynamics To evaluate this question, we used software to generate simulated targets with known flight dynamics similar to birds. We set as our success criterion that the demonstration would have achieved its objective if the targets displayed on the screen of the DRP matched the flight dynamics of the synthetic targets in the input data files. The goal of the second questions was to demonstrate whether the DRP can faithfully reproduce the plan position display of analog radar systems with which radar ornithologists are quite familiar. Here we directed the same raw analog signal from an operating X-band marine radar into the input of both an older analog BirdRad avian radar and a newer digital eBirdRad avian radar. This demonstration would be judged to be successful if the digital display of the scenes closely matched the analog display of the same scenes. 3.1.1.2.2 Provides Reduced Clutter Compared To Analog Radar [PA2.2] The antennas of avian radars are oriented close to horizontal in order to detect low-flying birds, and consequently, radar echoes from the ground, buildings, and other stationary objects (i.e., “ground clutter”) are a serious problem that can adversely affect the ability of the DRP to detect and track targets. To demonstrate the Accipiter® DRP can remove ground clutter from a scene while still detecting and tracking targets in that scene, we compared the images generated by the DRP when: A) The clutter suppression algorithms were turned off; B) the clutter suppression algorithms were turned on and the targets were “tracked” using the analog “true trails” display; and C) the clutter suppression algorithms were turned on and the targets were tracked digitally by the DRP. The would be judged successful if targets that were visible in the cluttered display were still visible in the uncluttered displays, targets that were not visible in the cluttered display were visible in the uncluttered displays, and all of these targets were tracked in the digital display. 3.1.2 Sampling Protocols Performance criteria in this category were designed to demonstrate that the digital avian radar systems evaluated by the IVAR project collect the types of data users require and can do so under the operating conditions that can be expected to be encountered at military facilities. 3.1.2.1 Quantitative Performance Criteria The performance objectives discussed in the following subsections were designed to evaluate sampling protocols quantitatively. That is, the Success Criteria were defined as a numeric quantity against which the results of testing the radar system could be evaluated. 3.1.2.1.1 Monitors and Records Bird Tracks 24/7 [PB1.1] A principal advantage of radar as a tool for sampling bird populations is its ability to operate continuously, day and night, collecting data under a wide range of environmental conditions. We designed Criterion PB1.1 to demonstrate this capability to sample continuously in the 38
temporal domain by recording all bird tracks at a given facility for a period of one week or longer. 3.1.2.1.2 Samples Birds 360° in Field Of View [PB2.1] Another advantage of radar as a sampling tool for birds is its ability to sample throughout a full 360° field of view around the radar. We designed Criterion PB2.1 to demonstrate this capability by showing that the numbers of birds tracked at various bearings from the radar were roughly the same over the course of a year (to allow for differences in diurnal and seasonal distribution of the birds). 3.1.2.1.3 Samples Out To 6 Nautical Miles [SB3.1] Criteria PA4.1 (Section 3.1.1.1.4) and PA5.1 (Section 3.1.1.1.5) were designed to demonstrate that avian radar systems can track birds within and immediately beyond the perimeter of most military airfields. We designed Criterion SB3.1 to demonstrate they can track birds out to a range of 11 km (6 nmi). This distance was chosen because one of the design specifications for the original BirdRad avian radar system was to sample in the range 0-11 km (0-6 nmi). 3.1.2.1.4 Efficiently Stores Bird Track Information [PB4.1] Recording a wide range of parameters for hundreds-to-thousands of birds that are being tracked 7/24, with a new track record being generated for each target 24 times a minute, could generate a volume of data that might overwhelm conventional data storage media. Criterion PB4.1 was designed to demonstrate that a year’s worth of plots and tracks data from a continuously operating avian radar system could be stored on a conventional data storage device. 3.1.2.1.5 Increase in Number of Birds Sampled [PB5.1] One would assume that digital avian radar systems, with their ability to sample continuously, day and night, through a 360° field-of-view, over ranges of 0-11 km and up to altitudes of a kilometer would sample more birds than visual observers using conventional sampling methods. We designed Criterion PB5.1 to test that assumption and we set as our success criterion that the radar would detect and track twice as many birds as the human observers. 3.1.2.1.6 Samples Up To 3000 Feet [SB6.1] Being able to track migrating birds is an important capability for both the natural resources management and the air safety applications for avian radar systems. Because migrating birds often fly at altitudes up to a kilometer (~3000 feet) or more, we designed Criterion SB6.1 to demonstrate that digital avian radar systems can track birds at those altitudes. 3.1.2.2 Qualitative Performance Criteria The performance objectives discussed in the following subsections were designed to evaluate sampling protocols qualitatively, with success criteria that could be defined in terms of “Achieved” or “Not Achieved”. 3.1.2.2.1 Sampling Of Diurnal and Seasonal Bird Activity Patterns [PB1.2] One advantage of digital avian radar systems is that they sample continuously day and night, and therefore can be used to build up historical records of short-, intermediate-, and long-term temporal bird activity patterns. To demonstrate this capability of the Accipiter® avian radar systems evaluated by the IVAR project, we proposed to use the plots and tracks data for a 24- 39
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FINAL REPORT Integration and Valida
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Table of Contents List of Tables ..
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APPENDIX A. POINTS OF CONTACT .....
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Table 6-17. Altitudinal distributio
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List of Figures Figure 2-1. Chronol
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Figure 6-17. Plot of the northing c
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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 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: For the third test, Validation Usin
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
Page 89 and 90: 5.3 DESIGN AND LAYOUT OF TECHNOLOGY
Page 91 and 92: Assuming these lines evidence confi
Page 93 and 94: that dataset [Section 6.5.1.3]. 5.5
Page 95 and 96: 6 PERFORMANCE ASSESSMENT The Perfor
Page 97 and 98: ecord the time, Track ID, and other
Page 99 and 100: Figure 6-1. Percentage of targets c
Page 101 and 102: Comparing the performance of dish v
Page 103 and 104: Figure 6-4. The basic sensor elemen
Page 105 and 106: Figure 6-6. The polygon around the
Page 107 and 108: Figure 6-8. Diagram of sampling “
Page 109 and 110: • It takes several scans (nominal
Page 111 and 112: Session Correla tions 600 500 y = 1
Page 113 and 114: To evaluate the capabilities of the
Page 115 and 116: 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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