DRDC CORA Task 016. RADARSAT-2 STK Model Automation. Kenzie MacNeil, Senior Technical Professional CAE Inc.

Transcription

1 Kenzie MacNeil, Senior Technical Professional CAE Inc. Prepared By: CAE Inc Innovation Drive Ottawa, Ont., K2K 3G7 Canada Contractor's Document Number: Version 02 PWGSC Contract Number: W /001/SV Technical Authority: Cheryl Eisler, Defence Scientist Disclaimer: The scientific or technical validity of this Contract Report is entirely the responsibility of the Contractor and the contents do not necessarily have the approval or orsement of the Department of National Defence of Canada. This document was reviewed for Controlled Goods by DRDC using the Guide to Canada s Export Controls. Contract Report DRDC-RDDC-2017-C015 January 2017

2 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

3 DRDC CORA TASK 016 RADARSAT-2 STK MODEL AUTOMATION CAE Inc Innovation Drive Ottawa, Ont., K2K 3G7 Canada Tel: Fax: CONTRACT #: W /001/SV FOR CHERYL EISLER Defence Scientist, MARPAC OR Team Defence Research and Development Canada Centre for Operational Research and Analysis Victoria, BC 1 3 J a n u a r y Document No Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017 RESTRICTION ON USE, PUBLICATION OR DISCLOSURE OF PROPRETIARY INFORMATION This document contains information proprietary to MacDONALD, DETTWILER AND ASSOCIATES LTD. (MDA), to its subsidiaries, or to a third part to which MDA may have a legal obligation to protect such information from unauthorized disclosure, use or duplication. Any disclosure, use or duplication of this document, or of any of the information contained herein for other than the specific purpose for which it was disclosed is expressly prohibited, except as MDA may agree to in writing.

4 A P P R O V A L S H E E T Document No Version 02 Document Name: DRDC CORA Task 016 Primary Author Name Position Kenzie MacNeil Senior Technical Professional CAE Inc. Reviewer Name Position Evan Harris Senior M&S Consultant CAE Inc. Approval Name Position Devin Duncan Project Manager International Safety Research 13 January 2017 ii Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

5 R E V I S I O N H I S T O R Y Revision Reason for Change Origin Date Version 01 DRAFT A Draft document issued for comment. 15 December 2016 Version 01 DRAFT B Revised to address client feedback. 23 December 2016 Version 01 Version 02 Finalized document; incorporated feedback. Minor corrections for publication as DRDC Contractor Report. 10 January January January 2017 iii Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

6 T A B L E O F C O N T E N T S 1 INTRODUCTION Background Objective Scope Outline MATLAB/STK MODEL DESIGN RADARSAT-2 KML Modelling in STK RADARSAT-2 KML Data RS2 KML Swath RS2 KML Swath Frame RADARSAT-2 STK Model RADARSAT-2 Constraint Interval Generation Algorithm Metrics Gathering Functionality STK Access Summary Report STK Footprint Area Report STK Percent Coverage Report MATLAB Sensor Area Coverage Report MATLAB Swath Interval Summary Report RS2 Geographic Angular Offset Metric Gathering Algorithm MATLAB IMPLEMENTATION CORA 016 MATLAB Functions Function applystkintervalfiles Function createnewcora016scenario Function findrs2sensorgeometryoffsets Function generateswathstkintervals Function getallfilesoftype Function isnorthwestpolygonccw Function radarsat2kmltocell CORA_016_KML_Files_to_STK_Scenario MATLAB Script RESULTS KML Sample Time Frame Results KML Sample Time Frame: 07 Oct 2016 to 13 Oct KML Sample Time Frame: 14 Oct 2016 to 20 Oct KML Sample Time Frame: 21 Oct 2016 to 27 Oct KML Sample Time Frame: 28 Oct 2016 to 03 Nov Script Performance Results January 2017 iv Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

7 4.2.1 Variable Analysis Time Step Value Performance Tests Variable Point Granularity Value Performance Tests DISCUSSION STK RS2 Misaligned Satellite Orbit Potential Future Work CONCLUSION REFERENCES APPENDIX A ACRONYMS AND ABBREVIATIONS... A-1 APPENDIX B INTERVAL DATA FOR KML SAMPLE... B-1 B.1 KML Sample Time Frame: 07 Oct 2016 to 13 Oct B-1 B.2 KML Sample Time Frame: 14 Oct 2016 to 20 Oct B-4 B.3 KML Sample Time Frame: 21 Oct 2016 to 27 Oct B-7 B.4 KML Sample Time Frame: 28 Oct 2016 to 03 Nov B-9 APPENDIX C MATLAB SCRIPTS... C-1 C.1 CORA_016_KML_Files_to_STK_Scenario... C-1 APPENDIX D MATLAB FUNCTIONS... D-1 D.1 applystkintervalfiles... D-1 D.2 createnewcora016scenario... D-6 D.3 findrs2sensorgeometryoffsets... D-21 D.4 generateswathstkintervals... D-47 D.5 getallfilesoftype... D-76 D.6 isnorthwestpolygonccw... D-78 D.7 radarsat2kmltocell... D-81 APPENDIX E TASK 016 RADARSAT-2 KML FILE...E-1 E.1 Task 016 Metric KML File...E-1 APPENDIX F EXAMPLE OF SCRIPT GENERATED STK INTERVAL FILE... F-1 F.1 CORA_016_ _to_ Radarsat2_DVWF_R_FieldOfView... F-1 13 January 2017 v Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

8 L I S T O F F I G U R E S Figure 2-1: Sensor Footprint and Swath Area Target STK Geographic Angular Offset.. 5 Figure 2-2: Example of Unadjusted RS2 KML Swath Start Time in STK... 6 Figure 2-3: Example of Unadjusted RS2 KML Swath Stop Time in STK... 6 Figure 2-4: Example of Coverage Aligned RS2 Swath Start Time in STK... 7 Figure 2-5: Example of Coverage Aligned RS2 Swath Start Time in STK... 8 Figure 2-6: Example of RS2 KML Swath in Google Earth... 9 Figure 2-7: Example of several RS2 KML Swath Frames in Google Earth Figure 2-8: Example of Swath Coverage Definition object in STK Figure 2-9: Example of Coverage Alignment when the Sensor is determined to be OFF Figure 2-10: Example of Coverage Alignment when the Sensor is determined to be ON Figure 2-11: Example of STK Access Summary Report Figure 2-12: Example of STK CORA_016_Sensor_Footprint_Area Report Figure 2-13: Example of STK CORA_016_Percent_Coverage Report Figure 2-14: Example of Sensor Area Coverage Report Figure 2-15: Example of Swath Interval Summary Report Figure 2-16: Example of Coverage Errors caused by RS2 Geographic Angular Offset 33 Figure 2-17: Example of a Clipped Sensor Beam Footprint Polygon Figure 2-18: Example of an Inner Coverage Error Polygon Figure 3-1: Example of Task 016 Script and Functions in MATLAB Figure 4-1: Script Execution Times with Variable Analysis Time Step Values Figure 4-2: Script Execution Times with Variable Point Granularity Values January 2017 vi Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

9 L I S T O F T A B L E S Table 2-1: RS2 KML Swath Description Element s Data Table 2-2: RS2 KML Swath Frame Description Element s Data Table 2-3: RADARSAT-2 STK Sensor Object Parameters Table 2-4: STK Access Report Style Properties Table 2-5: STK CORA_016_Sensor_Footprint_Area Report Style Properties Table 2-6: STK CORA_016_Percent_Coverage Report Style Properties Table 2-7: STK CORA_016_Sensor_Footprint_Points Report Style Properties Table 3-1: Input Parameters for applystkintervalfiles Table 3-2: Sensor Properties CSV Input File Structure Table 3-3: Input Parameters for createnewcora016scenario Table 3-4: Input Parameters for findrs2sensorgeometryoffsets Table 3-5: Output Parameters for findrs2sensorgeometryoffsets Table 3-6: Input Parameters for generateswathstkintervals Table 3-7: Output Parameters for generateswathstkintervals Table 3-8: Input Parameters for getallfilesoftype Table 3-9: Input Parameters for isnorthwestpolygonccw Table 3-10: Output Parameters for isnorthwestpolygonccw Table 3-11: Input Parameters for radarsat2kmltocell Table 3-12: Output Parameters for radarsat2kmltocell Table 3-13: Configuration Parameters for CORA_016_KML_Files_to_STK_Scenario. 48 Table 4-1: Task 016 Platform Specifications Table 4-2: Script Execution Times with Variable Analysis Time Step Values Table 4-3: Script Execution Times with Variable Point Granularity Values Table B-1: Interval Data for KML Sample Time Frame: 07 Oct 2016 to 13 Oct B-2 Table B-2: Interval Data for KML Sample Time Frame: 14 Oct 2016 to 20 Oct B-5 Table B-3: Interval Data for KML Sample Time Frame: 21 Oct 2016 to 27 Oct B-8 Table B-4: Interval Data for KML Sample Time Frame: 28 Oct 2016 to 03 Nov 2016 B January 2017 vii Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

10 A B S T R A C T The Maritime Forces Pacific (MARPAC) Operational Research Team requires the development of models of current and potential coastal surveillance platforms. These models need to be developed in the Systems Tool Kit (STK) Professional software to ensure required fidelity and reliability of the model. Several of these coastal surveillance models include the modelling of the RADARSAT-2 (RS2) satellite. Discrepancies in the RS2 modelled ground swath were previously found in [1] when comparing the results of the RS2 satellite object s sensors in the STK models and real-world Keyhole Mark-up Language (KML) swaths of ground passes. The objective of this task was to develop and implement a process to automate the application of STK temporal constraints and display time interval files such the RS2 sensor beam footprints coverage is aligned with swath geographic coordinate data from one or more RS2 KML input files. This process was implemented in MathWork s MATLAB R2015a scripting language. The MATLAB script made use of the STK software package version , STK Connect commands and STK Coverage Analysis. The MATLAB script and functions were successfully implemented to generate the coverage aligned STK RS2 interval files. A set of test STK scenarios that made use of RS2 temporal constraints display time files were generated for four sample timeframes, each of one week in duration, from a series of Technical Authority (TA)-provided RS2 KML files. Known limitations and suggestions for improvement were identified and documented. 13 January 2017 viii Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

11 1 INTRODUCTION This document is the final report developed for the project entitled RS2 STK Model Automation. This report was completed by CAE Inc. on behalf of International Safety Research (ISR) Inc. under Task 016 for contract #W /001/SV to Defence Research and Development Canada (DRDC) Centre for Operational Research and Analysis (CORA). 1.1 Background The Maritime Forces Pacific (MARPAC) Operational Research Team requires the development of models of current and potential coastal surveillance platforms. These models need to be developed in the Systems Tool Kit (STK) Professional software package version 11.0 (or higher) to ensure the required fidelity and reliability of the model. Several of these coastal surveillance models include the modelling of the RADARSAT-2 (RS2) satellite. Discrepancies in the RS2 modelled ground swath were previously found in [1] when comparing the results of the RS2 satellite object s sensors in the STK models and real-world Keyhole Markup Language (KML) swaths of ground passes. The use of the KML swath start and times in STK as inclusive temporal constraints and display times did not align the STK sensor beam footprint with the KML swath s geographical area. This caused large coverage area offsets/errors in the STK model. These offsets/errors varied by beam mode and scenario time. Prior to this task, manual offsets with linear correction factors, outlined in [1], were used to fix the coverage alignment issue on a case-by-case basis for individual swath analysis. 1.2 Objective The objective of this task was to develop and implement a process to automate the application of STK temporal constraints and display time interval files (.int) to ensure that the RS2 sensor beam footprints coverage is aligned with swath geographic coordinate data from one or more RS2 KML input files [2]. This process was developed in MathWorks s MATLAB scripting language, as it integrates well with STK and automates the execution of STK commands through MATLAB scripts and functions. The Technical Authority (TA) provided RS2 KML files for four sample timeframes, each of 1 week in duration. These sample timeframe KML files were to be processed and the results applied within the STK application to provide RS2 coverage aligned STK scenarios for the four sample timeframes. 1.3 Scope For this task, the process performed by the MATLAB scripts had the following minimum requirements: Connect to an existing STK session using STK Connect commands with MATLAB. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

12 Create a MATLAB script to import the RS2 satellite and sensor model from [1]. Create a MATLAB script to automatically set the scenario timeframe to be of one-week duration, as specified by the KMLs provided by the TA. Create a MATLAB script to automatically generate a new satellite object with the properties of the RS2 satellite (with sensors) as defined in [1], ensuring that the satellite database is up-to-date [3] before doing so. Create a MATLAB script to automatically compute the correction factors necessary to align the start and times of the sensor beams with the swath polygons from the KML files within +/- 0.5 s. The methodology for computing the correction factors must be generalized to work for any set of submitted KMLs. Create a MATLAB script to automatically update the RS2 temporal constraints and display time interval files (.int) based on the correction factors calculated from the KML files. 1.4 Outline This document contains the following sections: Section 1. Introduction: Describes the background, objective, and scope of the work conducted during this task. Section 2. MATLAB/STK Model Design: Describes the process used to generate coverage-aligned RS2 constraint intervals. Section 3. MATLAB Implementation: Describes the MATLAB scripts, functions, their activities, and their outcomes associated with the execution of the algorithm developed under this task. Section 4. Results: Summarises the results from the execution of the MATLAB scripts and functions developed under this task. Section 5. Discussion: Describes the limitations, known issues, and potential future work associated with the deliverables developed as part of this task. Section 6. Conclusion: Provides a summary of this task and its results. Section 7. References: Provides a list of references used in this report. Appix A. Acronyms and Abbreviations: Provides a list of the acronyms and abbreviations used in this document. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

13 Appix B. Interval Data for KML Sample: Contains the RADARSAT-2 STK interval data generated as part of this task for the different TA provided KML sample time frames. Appix C. MATLAB Scripts: Contains the source code for the MATLAB scripts developed under this task. Appix D. MATLAB Functions: Contains the source code for the MATLAB functions developed under this task. Appix E. Task 016 RADARSAT-2 KML File: Contains the content of a custom RS2 KML file generated as part of this task for performance analysis. Appix F. Example of Script Generated STK Interval File: Contains an example of the content of a STK constraint interval file (.int) produced for this task based on the TAprovided KML files. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

14 2 MATLAB/STK MODEL DESIGN This section contains a detailed description of the RS2 coverage alignment issues in STK and the data and process used to resolve these issues. 2.1 RADARSAT-2 KML Modelling in STK The RS2 satellite is an all-weather imagery and surveillance satellite, which is used for a wide range of civil, commercial and defence applications [4]. The RS2 satellite has a variety of imaging sensors [2][4], which observe and image the surface of the earth during its orbit. The finite geographic area of the earth s surface observed by the RS2 satellite during a specific time period is referred to as a swath. In [1], AGI s STK application was used to model the RS2 satellite for coverage analysis. As part of [1], a RS2 STK Satellite object was added from AGI s online satellite database. The default AGI RS2 satellite sensor objects were then modified based on TA-provided specifications. Realworld RS2 swath areas were then added as STK Area Target objects. The real-world RS2 swaths were produced by MDA and provided by the TA in Keyhole Mark-up Language (KML) files which outlined the sensor beam type, sensor orientation, imaging start time, imaging stop time and the rectangular geographic coordinates of the swaths. In [1], inclusive interval temporal constraints were applied to the RS2 sensor objects in STK to mimic the imaging start and stop time behaviour of the real satellite sensors. However, the raw RS2 KML start and stop times modelled in STK did not accurately represent the behaviour of the RS2 satellite and its imaging swaths in the KML data. The RS2 objects modelled in STK presented two types of coverage analysis discrepancies: a geographic angular offset and a temporal constraint interval offset. In [1], these discrepancies were addressed manually to align the RS2 sensor objects with the KML swath data to provide an accurate coverage analysis model of the real-world system in STK. The first and less important discrepancy observed in [1] was the geographic angular offset. This offset referred to the fact that the horizontal edges of the STK RS2 sensor beam footprints did not perfectly align with the horizontal edges of the STK swath Area Targets created using the KML coordinate data. This discrepancy/offset was most noticeable whenever the sensor footprint traversed the top or the bottom of the swath area target. The misalignment between the footprint and swath polygons caused minor coverage area errors in the form of triangles inside and outside of the STK swath Area Target. Figure 2-1 contains an exaggerated example of this type of geographical angular misalignment. In this example, the sensor footprint area is defined by the red rectangle and the swath area target is defined by the green rectangle. The green swath area target is considered a fixed geographic location 1. In contrast, the location of red sensor area footprint is constantly 1 Technically, the swath target area represents the area swept out by the actual sensor utilized onboard RS2, which the simulation is trying to reproduce. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

15 changing due to the orbit of the satellite. In this example, the sensor area footprint is aligned horizontally with the swath area target. The footprint starts at the top of the swath area and sweeps down the swath. Figure 2-1: Sensor Footprint and Swath Area Target STK Geographic Angular Offset The small coverage area error triangles produced by this misalignment in STK represented only a small portion of the overall sensor footprint s and swath area target s total area. In [1], it was decided that this coverage area error was an acceptable offset since there was no proposed solution to better align the sensor and area target polygon edges within STK. To mitigate this coverage area error, it was decided in [1] that the temporal constraint interval start and stop times should occur when the intersection point of the sensor footprint outer edge relative to the swath was in the middle of the swath area target s outer edge. This is type of intersection is also shown in Figure 2-1. This ted, on average, to cancel out the opposing extra-outer and missed-inner coverage errors. The second and the more important discrepancy outlined in [1] was the temporal constraint interval offset caused by applying the swath start and stop times listed in the KML file directly into the STK model. There were noticeable differences between the start and stop times listed in the RS2 KML files and the STK sensor interval times necessary for the STK sensor object s footprint to accurately represent the KML swath s geographic area. This discrepancy caused large coverage area errors in the STK model. For example, Figure 2-2 and Figure 2-3 represent a single case of the unaltered KML start and stop times, respectively, as the temporal constraints and display times applied to a RS2 sensor to align it with a KML swath area target. In this example, the raw KML interval times cause the sensor model to start imaging well before the swath s geographic area and stops imaging before reaching the of the swath s geographic area. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

16 Figure 2-2: Example of Unadjusted RS2 KML Swath Start Time in STK Figure 2-3: Example of Unadjusted RS2 KML Swath Stop Time in STK In [1] the discrepancies between the KML and STK swath intervals varied by beam mode and scenario time. One of the proposed solutions for addressing these discrepancies between the KML and STK swath intervals was to manually apply linear correction factors to KML swath intervals to fix the coverage alignment in STK. The fix to the swath s coverage alignment in STK was designed such that the STK sensor beam footprint should always be contained within the swath s geographic area. This approach ignores the resulting differences between the swath s duration value listed in the KML and the interval duration in STK. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

17 For example, Figure 2-4 and Figure 2-5 represent the coverage-aligned start and stop times, respectively, in STK for the original KML example in Figure 2-2 and Figure 2-3. In this example, the sensor footprint in STK is contained within the swath s geographic area but the overall interval duration in STK is noticeably smaller than in the KML. Currently, this model limitation is considered trivial because the focus of this task is on coverage analysis and not the analysis of sensor operational durations. Figure 2-4: Example of Coverage Aligned RS2 Swath Start Time in STK In the [1] model, the coverage alignment for swaths was implemented in STK using Temporal Constraints applied to the satellite sensor objects. These STK Temporal Constraints used a set of inclusive interval times, each defined by a start and stop time, to restrict the area a STK sensor object was imaging. In [1], these temporal constraint interval times were manually determined such that a STK sensor object would only be considered ON if its beam footprint was within a swath STK Area Target. Any STK Area Target considered for coverage alignment for a STK sensor object needed to match the STK sensor s beam type and satellite orientation. These manually calculated interval times were then added into STK temporal interval constraint files (.int) where a single interval constraint file existed for a single, specific RS2 STK sensor object. These temporal interval constraint files were used to restrict the access and display times of the STK sensor object. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

18 Figure 2-5: Example of Coverage Aligned RS2 Swath Start Time in STK 2.2 RADARSAT-2 KML Data The real world RADARSAT-2 sensor data provided by the TA as part of this task was expressed in KML files. KML is a XML based standard designed to express geographic annotations and visualization [5]. The KML standard was designed by Google and is an accepted Open Geospatial Consortium (OGC) standard [5]. KML files can be imported into applications including Google Earth, ArcGIS and AGI s STK to denote geographic areas, paths, overlays, etc. The RS2 KML files provided by the TA are expressed in version 2.2 of the KML standard. The RS2 KML files provided by the TA contain a series of geographic areas, which identify rectangular sections of the earth s surface previously imaged by the real world RS2 satellite sensors. These geographic areas are referred to as swaths. In the RS2 KML files, each realworld swath was recorded as a set of KML Placemarks elements. These KML Placemarks elements include smaller, component swath areas referred to as swath frames and a master, or complete, swath that is an amalgamation of the smaller swath frames. Figure 2-6 and Figure 2-7 contain examples of RS2 KML swath and swath frames, respectively, in the Google Earth application. NOTE: The master, or complete, swaths from hereon are simply referred to as swaths. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

19 Figure 2-6: Example of RS2 KML Swath in Google Earth In the RS2 KML file, each sensor swath is separated into its own KML Folder element. These folders are identified by the swath s start UTC time. This gives each KML swath folder a unique identifier as there is no overlap between different swaths start and stop times. Each folder contains only one master, or complete, swath KML Placemark and at least one swath frame KML Placemark. NOTE: NOTE: The RS2 swath frames are largely ignored by this task s MATLAB scripts because the swath frames contain redundant geographic area and time data for a given swath. Analysis of this redundant data by the scripts provided no meaningful benefit in the generation of the coverage aligned STK interval files. A specific RS2 swath does not exclusively exist in a single RS2 KML file. A swath may appear in different RS2 KML files deping on the RS2 KML type. For example, the MCSG and NRTSD RS2 KML data for the week of October 2016 provided by the TA shared two identical swaths. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

20 Figure 2-7: Example of several RS2 KML Swath Frames in Google Earth RS2 KML Swath This section contains a description of the swath Placemark data in the RS2 KML files. Each swath KML Placemark is composed of a KML name element, KML description element and a KML MultiGeometry Polygon element. The KML name element is a string containing the RS2 Swath ID value. An example of a KML name element is swath-1. The KML description element is a string containing all the relative RS2 data for the swath. The information in the description element is critical for modeling the swath in STK. The description contains the data outlined in Table 2-1. Each row in Table 2-1 is a separate line in the KML file. The row entries in Table 2-1 match the row ordering in the RS2 KML description elements. NOTE: The Swath ID string is not a unique identifier. A single RS2 KML file can have several swaths with the same ID. CAUTION: ANY CHANGES TO RS2 KML OR THE SWATH DESCRIPTION ELEMENT WILL NEGATIVELY AFFECT THE SCRIPT CREATED AS PART OF THIS TASK. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

21 Table 2-1: RS2 KML Swath Description Element s Data Description Line Item Satellite Swath ID Start UTC Time Stop UTC Time Start Abs. Orbit Value Description String identifying the satellite that produced the swath. This value should always be Satellite : RADARSAT-2. String identifying the swath. This value is not necessarily unique within a single KML file. Example: Swath ID: swath-1 UTC date-time identifying when the sensor was turned on to produce the finite swath area. The format of this date-time value is: yyyy-mmddthh:mm:ss.fffz where: yyyy is the year as 4 digits; mm is the month as 2 digits; dd is the day as 2 digits; T identifies that the following value is a time; HH is the UTC hour as 2 digits; MM is the UTC minute as 2 digits; SS is the UTC second as 2 digits; FFF is the UTC milliseconds as 3 digits; and Z identifies the UTC / Zulu time zone. Example: Start UTC Time: T03:04:05.678Z NOTE: This data is required in order to properly model a swath in STK. UTC date-time identifying when the sensor was turned off to produce the finite swath area. The format of this date-time value is: yyyy-mmddthh:mm:ss.fffz where: yyyy is the year as 4 digits; mm is the month as 2 digits; dd is the day as 2 digits; T identifies that the following value is a time; HH is the UTC hour as 2 digits; MM is the UTC minute as 2 digits; SS is the UTC second as 2 digits; FFF is the UTC milliseconds as 3 digits; and Z identifies the UTC / Zulu time zone. Example: Stop UTC Time: T23:59:59.999Z NOTE: This data is required to properly model a swath in STK. Real, positive number identifying the absolute orbit at the start of the swath. Example: Start Abs. Orbit: January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

22 Description Line Item Start Cycle, Rel. Orbit Duration (orbs) Duration (secs) Sensor Mode Beam Incidence Angle Tx Polarization Value Description Two real, positive numbers separated by a comma identifying the start cycle and relative orbit of the satellite. Example: Start Cycle, Rel. Orbit: 134, Real, positive number identifying the duration of the swath during the satellite s orbit. Example: Duration (orbs): Real, positive number identifying the duration of the swath in seconds. Example: Duration (secs): String identifying the top-level RS2 sensor mode that produced the swath. Possible sensor modes strings include: MSSR; ScanSAR Narrow; ScanSAR Wide; Wide; and Wide Fine. Example: Sensor Mode: MSSR String identifying the RS2 beam type that produced the swath. Possible beam strings include: DVWF; F0W1; F0W2; F0W3; OSVN; SCNA; SCNB; SCWA; W1; and W2. Example: Beam: DVWF NOTE: This data is required to properly model a swath in STK. Real, positive number identifying the incidence angle, in degrees, of the sensor for the swath. Example: Incidence Angle: Either a H, V or H+V string identifying the supported transmit polarizations for this beam. Example: Tx Polarization: H 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

23 Description Line Item Rx Polarization Pass Direction Satellite Orientation Reception Facility Main Priority Sub Priority Framing Value Description Either a H, V or H+V string identifying the supported receive polarizations for this beam. Example: Rx Polarization: H+V String identifying if the satellite orbit was Ascing or Descing while it was generating the swath. Example: Pass Direction: Ascing String identifying if the satellite was Right-looking or Left-looking while it was generating the swath. Example: Satellite Orientation: Right-looking NOTE: This data is required to properly model a swath in STK. String identifying the ground station reception facility where the data was downlinked and the imaging activity ID are supplied, [6]. Example: Reception Facility: CAAL Integer identifying the main RS2 mission priority level. Example: Main Priority: 20 Integer identifying the sub RS2 mission priority level. Example: Sub Priority: 10 String identifying the frame unit of the image swath, [6]. Example: Framing: ICEC Georeferenced The RS2 KML MultiGeometry Polygon element is used to define the geographic area of the swath. This definition contains an outerboundaryis sub-element that contains a LinearRing sub-element that contains a final coordinates element. The KML coordinates element is a single string that contains a series of location substrings. Either a new line or a space character separates these location substrings. The location substring format is the longitude value in degrees followed by the latitude value in degrees and an altitude value in meters separated by commas without any spaces. The substring , ,0 is an example of a single location. These locations in the RS2 KML coordinates element, when taken in sequential order, produce a rectangular, convex polygon defining the swath s geographic area. NOTE: The first and last location points are the same point in the RS2 KML coordinates element set. However, trying to add the same point to a polygon when it already exists in STK is not permitted and will cause STK errors RS2 KML Swath Frame A single swath is often composed of multiple swath frames. A single swath frame has a maximum duration of 75 seconds. Generally, if a swath has multiple swath frames then the swath has a longer duration and covers a greater area. Each swath frame Placemark is 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

24 composed of a KML name element, KML description element and a KML MultiGeometry Polygon element. The KML name element is a string containing the RS2 Swath ID and the frame number. The swath frame numbering for a given swath Folder starts at 1 and increases sequentially. An example of a swath frame s KML name element is swath-1-frame-1, and the next frame s name would be swath-1-frame-2. The KML description element is a string containing RS2 data for the swath frame. The description contains the data outlined in Table 2-2. Each row in Table 2-2 is a separate line in the KML file. The row entries in Table 2-2 match the row ordering in the RS2 KML description elements. Table 2-2: RS2 KML Swath Frame Description Element s Data Description Line Item Frame Frame Start UTC Time Frame Stop UTC Time Value Description Integer number identifying the sequential frame number for the swath. Example: Frame: 1 UTC date-time identifying the frame s start time. The format of this date-time value is: yyyy-mm-ddthh:mm:ss.fffz where: yyyy is the year as 4 digits; mm is the month as 2 digits; dd is the day as 2 digits; T identifies that the following value is a time; HH is the UTC hour as 2 digits; MM is the UTC minute as 2 digits; SS is the UTC second as 2 digits; FFF is the UTC milliseconds as 3 digits; and Z identifies the UTC / Zulu time zone. Example: Frame Start UTC Time: T03:04:05.678Z UTC date-time identifying the frame s stop time. The format of this date-time value is: yyyy-mm-ddthh:mm:ss.fffz where: yyyy is the year as 4 digits; mm is the month as 2 digits; dd is the day as 2 digits; T identifies that the following value is a time; HH is the UTC hour as 2 digits; MM is the UTC minute as 2 digits; SS is the UTC second as 2 digits; FFF is the UTC milliseconds as 3 digits; and Z identifies the UTC / Zulu time zone. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

25 Description Line Item Frame Start Abs. Orbit Frame Start Cycle, Rel. Orbit Frame Duration (orbs) Frame Duration (secs) Value Description Example: Frame Stop UTC Time: T23:59:59.999Z Real, positive number identifying the absolute orbit at the start of the swath frame. Example: Frame Start Abs. Orbit: Two real, positive numbers separated by a comma identifying the start cycle and relative orbit of the satellite for the frame. Example: Frame Start Cycle, Rel. Orbit: 134, Real, positive number identifying the duration of the swath frame during the satellite s orbit. The maximum value is orbs. Example: Frame Duration (orbs): Real, positive number identifying the duration of the swath frame in seconds. The maximum value is seconds. Example: Frame Duration (secs): RADARSAT-2 STK Model The RS2 STK model used in this task was a variation on the RS2 STK model outlined in [1]. Minor modifications were made to the [1] RS2 satellite object s sensors to support the MATLAB scripts created for this task: The [1] DVWF left and right sensor objects Rectangular Horizontal Half Angle values were changed from 10.5 deg to 2.0 deg. This was to unify the definition of the sensor with most of the other sensors in the model and avoid cases in STK where the sensor footprint was larger than the imported KML swath area. The [1] OSVN left and right sensor objects Rectangular Horizontal Half Angle values were changed from 12.2 deg to 2.0 deg. This was to unify the definition of the sensor with most of the other sensors in the model and avoid cases in STK where the sensor footprint was larger than the imported KML swath area. Instances of [1] sensor models with FOW in their name were changed to F0W. This involved changing the middle character from a capital o to a zero. This was to support string comparisons in the MATLAB scripts between the STK sensor object names and the beam type string in the KML files. The following set of sensor objects were added to the RS satellite object for this task: o o o Radarsat2_WideFine_W1_L_FieldOfView; Radarsat2_WideFine_W1_R_FieldOfView; Radarsat2_WideFine_W2_L_FieldOfView; and 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

26 o Radarsat2_WideFine_W2_R_FieldOfView. This was done to support KML beam types which did not previously appear in the [1] RS2 model. All RS2 sensor objects in this task used the STK Rectangular Sensor Type and Fixed Az-El Orientation with About Boresight set to Hold. The complete list of RS2 sensor object properties is shown in Table 2-3. Table 2-3: RADARSAT-2 STK Sensor Object Parameters STK Sensor Object Name Vertical Half Angle (deg) Horizontal Half Angle (deg) Pointing Azimuth (deg) Pointing Elevation (deg) Radarsat2_DVWF_L_FieldOfView Radarsat2_DVWF_R_FieldOfView Radarsat2_ExtedHigh_L_FieldOfView Radarsat2_ExtedHigh_R_FieldOfView Radarsat2_ExtedLow_L_FieldOfView Radarsat2_ExtedLow_R_FieldOfView Radarsat2_Fine_L_FieldOfView Radarsat2_Fine_R_FieldOfView Radarsat2_FineQuadPolarization_L_FieldOfView Radarsat2_FineQuadPolarization_R_FieldOfView Radarsat2_MultiLookFine_L_FieldOfView Radarsat2_MultiLookFine_R_FieldOfView Radarsat2_OSVN_L_FieldOfView Radarsat2_OSVN_R_FieldOfView Radarsat2_ScanSarNarrow_L_FieldOfView Radarsat2_ScanSarNarrow_R_FieldOfView Radarsat2_ScanSarWide_L_FieldOfView Radarsat2_ScanSarWide_R_FieldOfView Radarsat2_SCNA_FieldOfView Radarsat2_SCNB_FieldOfView Radarsat2_SCWA_FieldOfView Radarsat2_Spotlight_L_FieldOfView Radarsat2_Spotlight_R_FieldOfView Radarsat2_Standard_L_FieldOfView January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

27 STK Sensor Object Name Vertical Half Angle (deg) Horizontal Half Angle (deg) Pointing Azimuth (deg) Pointing Elevation (deg) Radarsat2_Standard_R_FieldOfView Radarsat2_Standard_S5_FieldOfView Radarsat2_Standard_S6_FieldOfView Radarsat2_StdQuadPolarization_L_FieldOfView Radarsat2_StdQuadPolarization_R_FieldOfView Radarsat2_UltraFine_L_FieldOfView Radarsat2_UltraFine_R_FieldOfView Radarsat2_Wide_L_FieldOfView Radarsat2_Wide_R_FieldOfView Radarsat2_WideFine_F0W1_L_FieldOfView Radarsat2_WideFine_F0W1_R_FieldOfView Radarsat2_WideFine_F0W2_L_FieldOfView Radarsat2_WideFine_F0W2_R_FieldOfView Radarsat2_WideFine_F0W3_R_FieldOfView Radarsat2_WideFine_W1_L_FieldOfView Radarsat2_WideFine_W1_R_FieldOfView Radarsat2_WideFine_W2_L_FieldOfView Radarsat2_WideFine_W2_R_FieldOfView Radarsat2_WideFineQuadP_L_FieldOfView Radarsat2_WideFineQuadP_R_FieldOfView Radarsat2_WideMultiFine_L_FieldOfView Radarsat2_WideMultiFine_R_FieldOfView Radarsat2_WideStdQuadP_L_FieldOfView Radarsat2_WideStdQuadP_R_FieldOfView Radarsat2_WideUltraFine_L_FieldOfView Radarsat2_WideUltraFine_R_FieldOfView Radarsat2_WideUltraFine_U18W2_FieldOfView Radarsat2_WideUltraFine_U24W2_FieldOfView RADARSAT-2 Constraint Interval Generation Algorithm This section contains a high-level overview of the process (algorithm) used to generate the STK interval files (.int) used to provide coverage alignment of RS2 KML data in STK. The following 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

28 RS2 constraint interval generation algorithm is designed around the functionality provided in the MATLAB and STK applications. The algorithm described in this section has been implemented in MATLAB as part of the CORA_016_KML_Files_to_STK_Scenario script. The first step in generating the constraint interval is to extract the necessary RS2 swath data from one or more RS2 KML files. For a swath to be added to our STK model, the following KML swath data needs to be extracted from the file(s): Start UTC Time; Stop UTC Time; Beam; Satellite Orientation; and Polygon Coordinates. This data extraction from the KML files results in a set of swath entries which span a given datetime range. The RS2 swath frames in the extracted data are ignored because they represent redundant geographic area and time data for an associated swath. This extracted swath data can now be used for coverage analysis within STK. As part of the coverage analysis process, a separate STK analysis scenario is generated for each KML file. This is done to limit the number of STK Coverage Definition objects within a given scenario. In previous STK releases, multiple STK Coverage Definition objects have put a strain on computer resources (such as CPU, RAM and storage). In rare cases, this strain would result in the STK application terminating unexpectedly. Each new STK analysis scenario is created using the earliest and latest times in the KML file to define the time the STK scenario s analysis period. These dates are taken to ensure that all swath times occur during the STK scenario s analysis period. For example, if the earliest and latest time in a KML file are T01:47:56.553Z and T01:39:06.859Z, respectively, then the STK scenario analysis period will be 07 Oct :00: to 11 Oct :59: The RS2 satellite object and associated sensor objects listed in Section 2.3 are then added to the new analysis scenario. The swaths in the KML file are then sequentially added and analyzed to determine the appropriate time constraint interval(s) for the swath in STK. A swath entry is first added to the STK scenario by creating a new STK Area Target object to represent the swath. This new swath Area Target is assigned the swath s KML coordinates to model the swath s geographic polygon in STK. The swath s associated STK RS2 sensor object is then selected by searching the set of satellite sensor names for matching swath beam string and matching satellite orientation character (i.e. L for Left-Looking and R for Right-Looking ). 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

29 If the appropriate satellite sensor object is found, then STK is queried for the set of Access Intervals between the Sensor and the Area Target. The STK Access Interval closest to the KML swath start and stop is identified. This closest Access Interval is then used as the analysis interval for the swath to limit the scope of the coverage analysis by minimizing the amount of scenario time analyzed for a specific swath. If the appropriate satellite sensor object is not found, then the swath is not processed and no associated interval times are produced for the swath. If the associated STK sensor object and the analysis interval has been determined then a new STK Coverage Definition object is created to perform STK coverage area analysis between the swath Area Target object and the associated RS2 Sensor object. The new Coverage Definition object contains the following properties: The analysis interval as the Coverage Definition s Analysis Interval; The RS2 Sensor object as the Coverage Definition s only Asset; The Coverage Definition is set to use Custom Regions and it is assigned the swath Area Target as the Bounds of its custom region; and The Grid Resolution s Point Granularity is set based on a static user defined value. This point granularity can be defined in terms of area between points in km 2, distance between points in km or latitude/longitude between points in degrees. Figure 2-8 contains an example of a swath Coverage Definition object in STK. The swath area target is defined by the white polygon and the Coverage Definition is defined by a series of blue points within the area target. NOTE: A smaller Point Granularity value will result in a finer grid resolution for the Coverage Definition. A finer grid resolution results in more time and resources being required by STK to compute the access for the Coverage Definition. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

30 Figure 2-8: Example of Swath Coverage Definition object in STK The swath Coverage Definition s Access is then computed by STK. Once computed, the Coverage Definition s Access is queried to determine the STK calculated Percent Coverage for the analysis interval and a user defined analysis time step. The STK Percent Coverage data provider identifies the amount of the Area Target coverage grid covered by the sensor footprint as a function of time. The queried Percent Coverage data provider contains a set of entries for each time step in the analysis interval. The Percent Coverage data retuned for each time step contains: The STK scenario UTCG time; The Percent Coverage which is the percentage of the Coverage Definition s Area Target region covered by the RS2 Sensor object at the reported time; The Area Coverage, in km 2, which is the area of the Coverage Definition s Area Target region covered by the RS2 Sensor object at the reported time; The Accumulated Percent Coverage of the Coverage Definition s Area Target region covered by the RS2 Sensor object up to and including the reported time; and The Accumulated Area Coverage, in km 2, of the Coverage Definition s Area Target region covered by the RS2 Sensor object up to and including the reported time. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

31 For the purposes of aligning sensor coverage with the swath area, we are only interested in the Percent Coverage data provider s Area Coverage values at each STK UTCG time step. The RS2 sensor object s Footprint Area data provider is also queried for the same analysis interval and analysis time step. The STK Footprint Area data provider returns the area on the earth s surface of a sensor beam s footprint. The queried Footprint Area data provider contains a set of entries for each time step in the analysis interval. The Footprint Area times will therefore match the time entries returned in the Percent Coverage query. The Footprint Area data returned for each time step contains: The STK scenario UTCG time; The Area, in km 2, of the sensor beam footprint on the earth s surface; The UTM Zone character indicator for the geodetic sub-point; The UTM Easting, the easting value within the UTM zone for the geodetic sub-point; The UTM Northing, the northing value within the UTM zone for the geodetic sub-point; and The MGRS Cell, which is the code for the cell area containing the geodetic sub-point. For the purposes of aligning sensor coverage with the swath area, we are only interested in the Footprint Area data provider s Area values at each STK UTCG time step. The Coverage Definition Percent Coverage s Area Coverage values and the Sensor Footprint Area s Area values are now used to determine what percentage of the RS2 Sensor object s footprint is inside of the swath Area Target for a given time step in the analysis interval. This is done by iterating through each set of matching STK UTCG Time entries and dividing the Percent Coverage s Area by the Footprint Area s Area. This returns the percentage of the RS2 Sensor object s beam footprint is inside of the swath Area Target. NOTE: A smaller analysis time step in STK will result in a finer set of coverage results. However, it will also require more time and resources to analyze the results. The Percentage of Beam Covered of each time step is then compared to a user defined static value identifying a Percentage Threshold for sensor coverage. If the Percentage of Beam Covered is below the Percentage Threshold, then the sensor footprint at this time step is too far outside of the swath area to be considered part of the aligned swath coverage interval. The sensor is therefore considered OFF during this time step. Conversely, if the Percentage of Beam Covered is greater or equal to the Percentage Threshold, then enough of the sensor footprint is inside the swath at this time step in order for the time step to be considered part of the aligned swath coverage interval. The sensor is therefore considered ON during this time step. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

32 NOTE: It is recommed that the Percent Threshold value assigned take into account the grid resolution point granularity value used in execution of the script. Larger point granularity values return less refined area coverage values which impacts the final sensor coverage percentage. In this case, it is recommed that a smaller Percent Threshold value be used with larger point granularity values. NOTE: It is possible that the calculated Percent of Beam Covered value can be larger than 100%. This can occur because of how STK determines its area coverage based on the Coverage Definition grid s point granularity resolution. For example, consider a swath Area Target and Sensor beam footprint at two different time steps. Let the Analysis Time Step be seconds, the Coverage Definition s Point Granularity be a distance of 2.5 km and the Coverage Percent Threshold be 97.5%. The analysis interval was determined to be 07 Oct :47: UTCG to 07 Oct :51: UTCG given the simple access calculation between the Area Target and Sensor objects. Figure 2-9 shows the sensor footprint at STK time 07 Oct :48:05.000, which is the 13 th time step entry in the Percent Coverage s Area Coverage values and the Footprint Area s Area values. At this time step the Percent Coverage s Area Coverage value is 13,332 km 2 and the Footprint Area s Area value is 32,605 km 2. Therefore, the calculated Percent of Beam Covered is 40.9%. This is below the threshold percentage of 97.5% so the sensor is considered to be OFF at this time step. Figure 2-9: Example of Coverage Alignment when the Sensor is determined to be OFF 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

33 Figure 2-10 shows the sensor footprint at STK time 07 Oct :48:12.000, which is the 27 th time step entry in the Percent Coverage s Area Coverage values and the Footprint Area s Area values. At this time step the Percent Coverage s Area Coverage value is 32,501 km 2 and the Footprint Area s Area value is 32,602 km 2. Therefore, the calculated Percent of Beam Covered is 99.7%. This is greater than threshold percentage so the sensor is considered to be ON at this time step. Figure 2-10: Example of Coverage Alignment when the Sensor is determined to be ON The collection of time steps where the calculated Percent of Beam Covered is greater or equal to the Percentage Threshold is considered to be the coverage aligned time constraint interval for the specific RS2 Sensor for the specific swath. The new coverage aligned time constraint interval for the swath is stored in MATLAB. This analysis process in STK is repeated until all swath entries in every selected KML file have been processed. Once all swath entries have been processed in the relative STK analysis scenario, the stored RS2 Sensor coverage aligned time constraint intervals are sorted and separated into new STK temporal interval constraint files. These temporal interval constraint files must be stored in the STK Interval List file format (.int). The STK Interval List File Format is an ASCII file which contains start and stop date-time pairs to define a series of time intervals. A new STK temporal interval constraint file is created for each swath beam and satellite orientation combination found in the KML file(s). This is done to match the constraint interval to the appropriate STK RS2 Sensor object. The intervals generated for each swath are added to the appropriate STK temporal interval constraint file. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

34 NOTE: It is possible that identical interval times are generated in different STK analysis scenarios. This can occur when a single unique KML swath appears in multiple KML files. In this case, a single interval entry is added to the STK constraint interval file and only one of the swath area targets is added to the final STK scenario. Once all of the STK temporal interval constraint files have been created, a new final STK scenario containing the results of the KML analysis is created. The new final STK scenario analysis interval is defined by the smallest and largest swath dates in all the KML files. All the STK Area Target objects created as part of the analysis scenarios are imported into the final STK scenario. The RS2 satellite object and associated sensor object listed in Section 2.3 are then added to the scenario. The STK temporal interval constraint files are then applied to the appropriate RS2 Sensor objects to align the RS2 sensor coverage with the RS2 swaths. Any RS2 Sensor without an interval file has an inclusive temporal constraint applied with zero time intervals which effectively sets the sensor to an OFF state for the duration of the STK scenario. 2.5 Metrics Gathering Functionality This section contains a high-level overview of this task s script and functions ability to generate reports and metrics on the generation of the coverage aligned interval for each KML swath processed by the algorithm described in Section 2.4. These features are enabled by setting the generatestkreports Boolean to true in the CORA_016_KML_Files_to_STK_Scenario script. The reports described in this section are generated and saved as part of Section 2.4 s STK analysis scenarios. All saved report files are contained within a Reports subdirectory of the specific STK analysis scenario directory. If reports are generated, then four different reports are generated per KML swath: A Default STK Access Summary Report; A Custom STK Footprint Area Report; A Custom STK Percent Coverage Report; A Sensor Area Coverage report generated by the CORA 016 MATLAB functions; and A Swath Interval Summary report generated by the CORA 016 MATLAB functions STK Access Summary Report The STK Access Summary report contains all the basic STK computed access between a specific RS2 Sensor object and a specific swath Area Target for the entire STK analysis scenario time period. This report uses the default STK Access report style. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

35 This default STK report consists of: The Local system time when the report was generated; The name of the STK Sensor and Area Target objects; A list of STK access entries between the two objects where each entry contains: o A sequential Access number starting at 1; o o o The Access Start Time (UTCG); The Access Stop Time (UTCG); The Duration (sec); A set of global statistics for the entire report: o o o o The STK access entry with the shortest access duration; The STK access entry with the longest access duration; The average STK access duration; and The total STK access duration. The STK Access Summary reports are named by the time data of the STK swath Area Target and the substring Access. For example, the Access Summary report for a STK Area Target swath called _0200_11935_ScanSAR_Narrow_SCNA_R would be _0200_11935_Access.txt. Table 2-4 shows the elements in the STK Access Report. Figure 2-11 contains an example of an STK Access Summary report. Report Section Table 2-4: STK Access Report Style Properties Data Provider Item Data Provider Units Section 1 / Line 1 Access Data Access Number N/A Section 1 / Line 1 Access Data Start Time UTCG Section 1 / Line 1 Access Data Stop Time UTCG Section 1 / Line 1 Access Data Duration sec 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

36 Figure 2-11: Example of STK Access Summary Report STK Footprint Area Report The STK Footprint Area report describes the area of the RS2 Sensor object s beam projection on the surface of the earth for a specific analysis interval and time step. This report uses a custom STK report style generated for this task called CORA_016_Sensor_Footprint_Area. The associated STK report style file called CORA_016_Sensor_Footprint_Area.rst must be present in the STK application s Config\Styles\Sensor subfolder for the MATLAB functions to generate this report. This custom STK report consists of: The Local System Time when the report was generated; The name of the STK Sensor object; A list of STK time steps entries during the access interval where each entry contains: o o The STK scenario UTCG time; The Area, in km 2, of the sensor beam footprint on the earth s surface; A set of global statistics for the entire report: o o o The STK time step with the smallest Footprint Area; The STK time step with the largest Footprint Area; and The average Footprint Area (km 2 ) for the access interval. The STK Footprint Area reports are named by the time data of the STK swath Area Target and the string Footprint_Area. For example, the Footprint Area report for a STK Area Target swath 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

37 called _0200_11935_ScanSAR_Narrow_SCNA_R would be _0200_11935_ Footprint_Area.txt. Table 2-5 shows the elements in the custom STK Footprint Area. Figure 2-12 contains an example of an STK Footprint Area report. Table 2-5: STK CORA_016_Sensor_Footprint_Area Report Style Properties Report Section Data Provider Item Data Provider Units Section 1 / Line 1 Time UTCG Section 1 / Line 1 Footprint Area Area km Figure 2-12: Example of STK CORA_016_Sensor_Footprint_Area Report STK Percent Coverage Report The STK Percent Coverage report contains a Coverage Definition s Percent Coverage given a computed access for a specific analysis interval and time step. This report uses a custom STK report style generated for this task called CORA_016_Percent_Coverage. The associated STK report style file called CORA_016_Percent_Coverage.rst must be present in the STK application s Config\Styles\CoverageDefinition subfolder for the MATLAB function to generate this report. This custom STK report consists of: The Local System Time when the report was generated; 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

38 The name of the STK Coverage Definition object; A summary of the STK Coverage Definition object s properties; A list of STK time steps entries during the access interval where each entry contains: o o o o o The STK scenario UTCG time; The Percent Coverage of the Coverage Definition s Area Target region covered by the RS2 Sensor object at the reported time; The Area Coverage, in km 2, of the Coverage Definition s Area Target region covered by the RS2 Sensor object at the reported time; The Accumulated Percent Coverage of the Coverage Definition s Area Target region covered by the RS2 Sensor object up to and including the reported time; and The Accumulated Area Coverage, in km 2, of the Coverage Definition s Area Target region covered by the RS2 Sensor object up to and including the reported time. A set of global statistics for the entire report: o o o o The STK time step with the smallest Percent Coverage; The STK time step with the largest Percent Coverage; The average Percent Coverage during the access interval; and The average Area Coverage (km 2 ) for the access interval. The STK Percent Coverage reports are named by the time data of the STK swath Area Target and the string Percent_Coverage. For example, the Percent Coverage report for a STK Area Target swath called _0200_11935_ScanSAR_Narrow_SCNA_R would be _0200_11935_ Percent_Coverage.txt. Table 2-6 shows the elements in the custom STK Percent Coverage. Figure 2-13 contains an example of an STK Percent Coverage report. Report Section Table 2-6: STK CORA_016_Percent_Coverage Report Style Properties Data Provider Item Data Provider Units Section 1 / Line 1 Coverage Definition Coverage Properties N/A Section 2 / Line 1 Percent Coverage Percent Coverage N/A Section 2 / Line 1 Percent Coverage Area Coverage km 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

39 Report Section Data Provider Item Data Provider Units Section 2 / Line 1 Percent Coverage Percent Accum Coverage N/A Section 2 / Line 1 Percent Coverage Accum Area Coverage km Figure 2-13: Example of STK CORA_016_Percent_Coverage Report MATLAB Sensor Area Coverage Report The Sensor Area Coverage report is a MATLAB-generated report that contains the sensor coverage analysis performed in MATLAB. This coverage analysis report outlines whether or not a sensor is considered ON for a specific time step as well as an additional estimate of the coverage error caused by the geographic angular offset described in Section 2.1. The report consists of: The MATLAB and STK parameters used when performing the sensor coverage analysis; 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

40 The Local System Time when the report was generated; References to the raw KML swath data used to generate the Area Target being used for the sensor coverage analysis; The name of the STK Sensor object; A list of STK time steps entries during the access interval where each entry contains: o o o o o o o o o The STK scenario UTCG time; The Percent Coverage data set s Area Coverage, in km 2, of the Coverage Definition s Area Target region covered by the RS2 Sensor object at the reported time; The Footprint Area data set s Area, in km 2, of the sensor beam footprint on the earth s surface at the reported time; The calculated Percent of Beam Covered taken by dividing the Area Coverage by the Footprint Area at the reported time; A Boolean indicating if the sensor is considered ON at the reported time given the calculated Percent of Beam Covered and the Percentage Threshold; The calculated estimate of the Sensor Beam Area Outside, in km 2, of the swath Area Target at the reported time given the metric algorithm outlined in Section 2.5.6; The calculated estimate of the Sensor Beam Percent Outside of the swath Area Target taken by dividing the Beam Area Outside by the Sensor Footprint Area; The calculated estimate of the inside gap area, in km 2, between the Sensor Beam and the swath Area Target at the reported time given the metric algorithm outlined in Section 2.5.6; and The calculated estimate of the percent of the inside gap given the Sensor Footprint Area taken by dividing the inside gap area by the Sensor Footprint Area. The STK Sensor Area Coverage reports are named by the time data of the STK swath Area Target and the string Sensor_Area_Coverage. For example, the Footprint Area report for a STK Area Target swath called _0200_11935_ScanSAR_Narrow_SCNA_R would be _0200_11935_Sensor_Area_Coverage.txt. Figure 2-14 contains an example of a Sensor Area Coverage report. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

41 Figure 2-14: Example of Sensor Area Coverage Report MATLAB Swath Interval Summary Report The Swath Interval Summary report is a MATLAB-generated report that contains a summary of the STK swath interval times produced for a given STK analysis scenario. The report consists of: The MATLAB and STK parameters used when performing the sensor coverage analysis; A list of STK interval times generated for all the processed swaths in a KML file where each entry contains: The STK swath Area Target name; The swath beam mode; The swath satellite orientation where R indicates Right-Looking and L indicates Left- Looking ; The KML start time of the swath; The KML time of the swath; The start time of the interval in STK; The time of the interval in STK; and 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

42 The accumulated swath coverage percent of the coverage definition by the sensor footprint for the STK interval s start and times. Only one Swath Interval Summary report is generated for a STK analysis scenario. Figure 2-15 contains an example of a Sensor Area Coverage report. Figure 2-15: Example of Swath Interval Summary Report RS2 Geographic Angular Offset Metric Gathering Algorithm This section describes the algorithm used to estimate the coverage error caused by the geographic angular offset between the sensor footprint and KML swath polygons for a specific time step. The geographic angular offset between the polygons is described in Section 2.1. This metric gathering algorithm is composed of two separate component algorithms. The first component algorithm determines the coverage error area, in km 2, of the sensor beam footprint outside of the swath Area Target. The second component algorithm uses the result of the first algorithm to determine the coverage error area, in km 2, inside the swath Area Target that was missed by the sensor beam footprint. These two areas are shown in yellow in Figure This coverage error metric was requested by the TA. Unfortunately, STK does not provide the necessary functionality to retrieve these coverage error areas. As such, the majority of the associated geographic analysis takes place within MATLAB to determine the extra sensor area outside of the swath and the missed area inside the swath. These geographic MATLAB calculations resulted in minor estimation errors when applied back into STK. Additional information concerning the algorithm s estimation errors can be found in Section January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

43 Figure 2-16: Example of Coverage Errors caused by RS2 Geographic Angular Offset RS2 Geographic Angular Offset Outer Coverage Error Algorithm This section describes how the estimated outer coverage error area, in km 2, is calculated within MATLAB and STK. The Sutherland-Hodgman polygon clipping algorithm is to determine the sensor beam area outside of the swath Area Target. The concept of polygon clipping is to restrict a geometric primitive to within a specific region of interest. In this case, the Sutherland- Hodgman algorithm is used to determine the geographic points of the sensor footprint polygon within the swath Area Target region of interest. For example, this polygon clipping would reduce the red sensor footprint polygon in Figure 2-16 to the orange clipped sensor polygon in Figure By taking the difference in area between the complete and clipped sensor footprint polygons, we are able to determine the area outside of the swath Area Target at any given time step. The first step in executing the Sutherland-Hodgman polygon clipping algorithm is to extract the STK sensor footprint s intersection points with the earth s surface for a specific time step. These intersection points are the set of latitude and longitude values that define the footprint polygon in STK for a specific STK UTCG time. These points are queried in STK through the Pattern Intersection data provider. This set of points can also be examined in STK through the custom CORA_016_Sensor_Footprint_Points report style outlined in Table 2-7. The footprint and swath polygons are then applied to the Sutherland-Hodgman polygon clipping algorithm. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

44 Figure 2-17: Example of a Clipped Sensor Beam Footprint Polygon Table 2-7: STK CORA_016_Sensor_Footprint_Points Report Style Properties Report Section Data Provider Item Data Provider Units Section 1 / Line 1 Pattern Intersection Latitude deg Section 1 / Line 1 Pattern Intersection Longitude deg Section 1 / Line 1 Pattern Intersection Altitude km Section 1 / Line 1 Pattern Intersection Distance Along Ground Track km Section 1 / Line 1 Pattern Intersection Distance Perp To Ground Track km The Sutherland-Hodgman algorithm implementation used in this task is designed to process simple, convex polygons. Essentially, the Sutherland-Hodgman clipping algorithm iterates through both sets of polygon edges and if sensor edge intersects a swath edge, then the sensor edge needs to be clipped. A sensor edge is clipped by determining the sensor vertex outside of the swath edge by taking the cross product and then replacing the outside vertex with an intersection point between the sensor and swath edges. The MATLAB functions in this task use geographic calculations outlined in [7] to calculate the cross product and intersection point given the latitude values, longitude values and the WGS84 ellipsoid. The MATLAB implementation of these calculations have certain restrictions on the sensor and swath polygons. The cross product and intersection point calculations are only designed to process geographical points within the North-West quadrant of the earth. Furthermore, the cross product calculation in this algorithm requires that all the vertices in the polygons be listed in a counter-clockwise direction. It should also be noted that the [7] calculations used to determine the intersection points do not translate perfectly back into STK. The MATLAB calculated intersection points in STK have an 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

45 (empirically determined) error of roughly ± 5.5 km. As such, any calculated outer coverage error area of 35 km 2 or less is ignored by this task s MATLAB functions. CAUTION: THE IMPLEMENTED CROSS PRODUCT AND INTERSECTION POINT CALCULATIONS ARE ONLY VALID FOR POLYGONS CONTAINED WITHIN THE NORTH-WEST QUADRANT OF THE EARTH. THE PROCESSING OF ANY POINT WHICH DOES NOT HAVE A POSITIVE LATITUDE AND A NEGATIVE LONGITUDE VALUE WILL GENERATE INCORRECT OR INVALID METRICS. Once the Sutherland-Hodgman algorithm is complete and MATLAB has generated the clipped sensor polygon, the script adds the clipped sensor polygon to the STK analysis scenario as a temporary Area Target object. STK is then queried for the area, in km 2, of the temporary clipped sensor area target. This determines an accurate area of the sensor footprint inside the swath. This allows the sensor area outside of the swath to be calculated by taking the difference between the total footprint area and the calculated area within the swath. This method of calculating the outer coverage error provides a more accurate area value than simply subtracting the Sensor Footprint Area by the Area Target Covered by Sensor for a given time step. Often the precision of the STK coverage definition computed access area is too poor to accurately determine the area of the small footprint percentage outside of the swath. This is especially true when the coverage definition s grid resolution is very low RS2 Geographic Angular Offset Inner Coverage Error Algorithm This section describes how the estimated inner coverage error area, in km 2, is calculated within MATLAB and STK. The algorithm for finding the inner coverage error area is much simpler but it has several restrictions. The algorithm is only executed under the following conditions: The clipped sensor polygon produced by the outer coverage error algorithm did not match the original sensor polygon (i.e. the footprint is completely contained within the swath polygon). There is only one corner from the original sensor polygon missing from the clipped polygon (i.e. an inner coverage error triangle is produced by the RS2 geographic angular offset). The sensor and swath polygons must have a rectangular shape. The clipped polygon produced by the RS2 Geographic Angular Offset Outer Coverage Error Algorithm must have a coverage error area of more than 35 km 2. If these conditions are met, then the MATLAB scripts use the clipped polygon and swath polygon to generate a new inner coverage error polygon. For example, the inner error polygon for the red sensor footprint polygon in Figure 2-16 is the purple polygon in Figure January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

46 Figure 2-18: Example of an Inner Coverage Error Polygon This new inner coverage error polygon is created using the following four points: The sensor polygon corner inside of the swath where the edge to the opposing sensor corner vertex was removed in the clipping polygon. The swath polygon corner closest to the selected sensor polygon corner. The intersection point from the clipped sensor polygon which is closest to the sensor and swath selected corners. A calculated intersection point between a ray leaving the selected sensor corner and the side of the swath polygon. Once the inner polygon points are selected in MATLAB, the script adds the inner coverage error polygon to the STK analysis scenario as a temporary Area Target object. STK is then queried for the area, in km 2, of the temporary inner coverage error area target. The results of this algorithm are also subject to a (empirically determined) distance error of roughly ± 5.5 km between the location generated by the implemented [7] calculations described in Section and the expected location in STK. 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017

47 3 MATLAB IMPLEMENTATION This section contains descriptions of the MATLAB deliverable developed for Task 016. The MATLAB deliverable consists of a single MATLAB script and seven MATLAB functions. The script and functions are designed to convert one or more RS2 KML files into coverage aligned STK constraint interval files (.int) and apply the interval files to a single STK scenario. This is achieved by applying the algorithms outlined in Section 2 to the RS2 KML data and STK RS2 model. An example of the task scripts and functions in the MATLAB application can be found in Figure 3-1. Figure 3-1: Example of Task 016 Script and Functions in MATLAB 13 January Version 02 Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défense nationale, 2017