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

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4. Extract a one-hour time segment at each of the beginning, middle, and the end of the oneweek period. Each one-hour segment will have approximately 1500 radar scans for each radar. 5. Load the extracted scan times for the pair of radars into a spreadsheet for comparison. 6. Analyze time differences (ignoring missed entries) between radars by computing for each one-hour segment the average pair-wise time difference between successive radar scan times. This average time difference is a measure of the temporal misalignment for the given one-hour segment. 7. The maximum temporal misalignment computed for any one-hour segment should not exceed two (2) times the scan-period which equals 2*2.5 = 5 seconds. In other words, the pair of radars over the one week period should remain time aligned as measured in the RDS to within 5 seconds or two scan periods, accounting for differences in latencies between the pair of radars. Fusion Processing Procedure (SD5.1) 1. Identify at least five paired sets of time-aligned track data from two radars with overlapping coverages that include simultaneous tracking of the same target(s). From each paired set of track data, select a segment that includes the simultaneously tracked targets and has a duration of at least 5 minutes. Record the duration of each of the five paired segments of track data (i.e., the five “datasets”) to the nearest second. 2. Repeat Step #3 through Step #7 below for each of the five paired datasets 3. Use the Multi-Radar Fileserver to serve the paired target track data to the Radar Fusion Engine, or RFE (ARTI beta software). 4. Press the start button on the RFE to begin processing the paired track data, while at the same time activating a timer to record the RFE processing time. The RFE will associate overlapping duplicate tracks to filter them so as to demonstrate the elimination of track duplicates. The RFE will also demonstrate in the same manner the increase in track continuity afforded by fusion. 5. Display the original paired tracks and resulting fused tracks (see Nohara, et al., 2008) using the RFE’s display capabilities to capture the above demonstrations and report on them. 6. Stop the timer when the RFE completes the processing of the paired track data. Record to the nearest second the time the RFE required to process the paired track data. 7. Compare the RFE processing time as measured by the timer in Step #6 with the realtime duration of paired track data as recorded in Step #1. The RFE processing time should be less than or equal to the real-time duration of the paired track data. 332
APPENDIX C. DATA QUALITY ASSURANCE/QUALITY CONTROL PLAN Quality Assurance Narrative Statement: The proposed research will conform to published agency guidance. Considering the field-based data collection activities, a model in the USEPA policy statements provided by the National Center for Environmental Research and Quality Assurance will be used for this project. Specific quality assurance program elements will be based on the latest version of EPA QA/R-5, Requirements for Quality Assurance Project Plans. Quality Assurance (QA) on this project has two elements. The first is the QA program implemented by project principals, the second is a QA program monitoring conducted by a Unit QA officer. Program implementation is described below. The Unit QA officer, Mr Gerry Key will provide monitoring to assure that the QA plan and QA activities conform to published guidance. Activities performed, hypotheses tested, and criteria for determining the acceptability of data quality. This research is designed to collect new data and will use existing data resources, modeling approaches, and other methods to validate the use of radar systems in natural resources management (NRM) and Bird Aircraft Strike Hazard (BASH) activities. Hypotheses to be tested are associated with the performance of radar systems, and individual system technologies in the detection and tracking of bird targets, and the validation steps necessary to assure utility to NRM and BASH programs. As part of quality assurance plans, all data collection activities will be guided by defined performance criteria as presented in “Field Demonstrations of the Operational Capabilities of Digital Avian Radar Systems. The acceptability of data quality will be judged against defined performance objectives. The study design The project has a study design intended to fully validate the use of avian radars in NRM and BASH applications. An initial QA element of this project is the review of this proposal and a ESTCP review of the initial report and demonstration plan submission. QA elements also include development of a quality assurance program by project principals, regular review by collaborators so that focus on critical issues is maintained throughout the project, and the review of the Unit QA officer to assure overall project conformance with QAPP requirements. Procedure for handling and custody of samples This research will involve field sampling and a protocols and procedures will be developed based on objectives and performance criteria. All data sources will be identified, catalogued, and documentation will be kept listing data use in each of the modeling/analysis steps of the validation program. 333
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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
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Figure 6-82. Hourly track count ove
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Figure 6-115: COP display showing f
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List of Acronyms Acronym AGL AIP AR
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Acronym RST RT SEA SQL SSC Pacific
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Carmen Lombardo Naval Air Station,
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EXECUTIVE SUMMARY Military bases an
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database and redistributed to other
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1 INTRODUCTION 1.1 BACKGROUND Encro
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A seventh objective, the Functional
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Table 1-1 (cont.). IVAR TASK/ OBJEC
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environmental stewardship with miss
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2 TECHNOLOGY/METHODOLOGY DESCRIPTIO
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The original BirdRad system was des
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2.4 TECHNOLOGY/METHODOLOGY DEVELOPM
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Figure 2-2. Configuration of BirdRa
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2.4.3 eBirdRad - Digital Radars wit
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Figure 2-5. Interior view of the eB
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accuracy and target continuity over
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permanently installed at SEA. Prior
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2.5 ADVANTAGES AND LIMITATIONS OF T
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3 PERFORMANCE OBJECTIVES Table 3-1
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Table 3-1 (cont.). Performance Obje
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For the third test, Validation Usin
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temporal domain by recording all bi
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3.1.2.2.7 Provides Bird Abundance o
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difference in the time (i.e., the l
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3.1.6.2.4 Maintenance [SE4.2] We es
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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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Page 307 and 308: e incurred, depending on what infor
Page 309 and 310: eal time, avian radars and can dete
Page 311 and 312: Network Connectivity. The US Depart
Page 313 and 314: Airport Improvement Program (AIP) f
Page 315 and 316: 9 REFERENCES Anderson, C., and S. O
Page 317 and 318: APPENDIX A. POINTS OF CONTACT POINT
Page 319 and 320: POINT OF CONTACT Name Ryan King Mat
Page 321 and 322: APPENDIX B. ANALYTICAL METHODS SUPP
Page 323 and 324: METHOD #2: VALIDATION BY IMAGE COMP
Page 325 and 326: The pattern of yellows and blues in
Page 327 and 328: Radar Team (RT) Site Selection Sinc
Page 329 and 330: will measured the magnetic bearing
Page 331 and 332: Figure B-6. Using a GPS to record s
Page 333 and 334: • Visual Observer - observes bird
Page 335 and 336: Figure B-9. Flowchart of target con
Page 337 and 338: VT: “Radar, Team 2-Alpha copies T
Page 339 and 340: eam and the VTs have difficulty loc
Page 341 and 342: why it was changed, who made the ch
Page 343 and 344: METHOD #4: CONFIRMATION OF BIRD TAR
Page 345 and 346: Figure B-12. Duplexed image showing
Page 347 and 348: Table B-2. Dates, times, and antenn
Page 349 and 350: For the analysis of the simultaneou
Page 351 and 352: Table B-3. Altitude of the radar be
Page 353 and 354: Figure B-17. Diagram of sampling
Page 355: METHOD #6: DEMONSTRATING REAL-TIME
Page 359 and 360: APPENDIX D. SUPPORTING DATA D.1 Par
Page 361 and 362: Table D-1 (cont.). Date Track ID Up
Page 367 and 368: D.2 Listing of One-Hour Track Histo
Page 369 and 370: Table D-2 (cont.). 07:00-08:00 WI_A
Page 371 and 372: APPENDIX E. SURVEY OF AIRPORT PERSO
Page 373 and 374: used as the real-time target becaus
Page 375 and 376: Table E-1. Remote radar display lat
Page 377: 7. Please rate the following where
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