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

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Figure 4-9. ARTI, showing location of radar tower near corporate offices. We designated ARTI as the “operations center” for the IVAR data streaming and data fusion/integration demonstrations. We elected to locate the Radar Data Server (RDS) there to serve as the destination for streaming, storing, and redistributing data to other sites and applications, including the Radar Fusion Engine (RFE). ARTI also has locally installed radars, including an eBirdRad with both wired and wireless links to the RDS. 57
5.1 CONCEPTUAL TEST DESIGN 5 TEST DESIGN This section describes the tests we designed to demonstrate the six project objectives of the IVAR project, as described in Section 1.2 and Table 3-1. Figure 2-7 provides a diagrammatic representation of the major components of the avian radar systems the IVAR project used to demonstrate those stated objectives. For conveniences, Figure 2-8 summarizes in a single diagram how all of these components might be deployed in an operational environment: In the actual tests, we deployed different combinations of components at a single location, while other situations required communications between components at several facilities. Section 5.4 organizes the design of the tests the IVAR project developed to evaluate avian radar systems into categories based on the major performance objectives listed in Table 3-1, which are in turn derived from the user requirements summarized in Table 1-1. At the highest level, these tests were designed to answer three fundamental questions about the avian radar systems that are on the market today (or at least those evaluated by this project): Do they perform as advertised Digital avian radar systems are relatively new technology (Figure 2-1). They were not developed following conventional “build-to-spec” protocols, nor are there any “industry standards” for these systems. In short, most of what a potential end-user might want to know about these systems came from vendor literature or anecdotal observations. Thus, the first high-level grouping of the tests the IVAR project designed asked the fundamental question: what are the capabilities of digital avian radar systems In particular, are the targets the software is tracking really birds Can they track birds in real time At what range, through what field-of-view, and to what altitude can these systems reliably track birds Can they perform under real-world conditions Given these systems perform as advertised, can they do so continuously and reliably, 24/7, in different geographic regions, by personnel with little or no prior experience Can they be operated automatically and remotely How many birds can they track at once and are they likely to detect at least as many birds as a human observer would Can multiple radars be operated simultaneously to cover large facilities Can they deliver the data where, when, and in the form they are needed What types of data will be available for each target, and will they be available in real time How can those data be presented to the users: visually, graphically, in tabular form, and/or exported to thirdparty products Can the real-time data be reliably streamed across a network and stored in a database for redistribution and/or historical analysis Can tracks from multiple radars be integrated into a common display or fused into common tracks Can alarms be set to notify users when an event occurs, without having to constantly monitor the radar A fundamental design question was raised early in the IVAR project, one that pertains to radars in general; namely, the probability a radar can detect a real target that is present in the radar beam, or conversely, the probability that noise, clutter, or other factors can cause the radar to report the detection of a target that isn’t really there - a “false detection”. This issue is a particularly important issue for avian radar systems because birds are small, highly maneuverable, and poor radar reflectors. In order to detect and track as many birds as possible, 58
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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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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
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: location for demonstrating the capa
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
Page 117 and 118: comparisons between the RCH-GPS dat
Page 119 and 120: Figure 6-18. Plot of the northing c
Page 121 and 122: Figure 6-20. Plot of the easting co
Page 123 and 124: Conclusion In the quantitative perf
Page 125 and 126: Table 6-8. Column headings of the T
Page 127 and 128: Table 6-9 demonstrates quantitative
Page 129 and 130: Table 6-10. The parameters of targe
Page 131 and 132: Table 6-11. The position of Visual
Page 133 and 134: Table 6-12. Solitary targets at MCA
Page 135 and 136: Figure 6-23. The track of target T2
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Figure 6-25. 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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