Recipient Organization
TRIDENT SENSING LLC
8475 WEBER DR
KAMAS,UT 84036
Performing Department
(N/A)
Non Technical Summary
Climate change is increasing the frequency and severity of western wildfires. The threat to people and infrastructure is growing with more population living in the wildland-urban interface. Advances in technology provide the opportunity to improve wildfire mapping accuracy, timeliness and dissemination. An un-stabilized airborne fire mapping sensor is proposed utilizing an array of miniature thermal infrared and color cameras providing near hemispherical downward-looking coverage. A solid-state Inertial Navigation System (INS) is included to provide accurate sensor orientation for geo-referencing fire mapping data. The sensor is small and light enough to be conformal mounted on every airborne firefighting asset making all participating aircraft fire mapping nodes. An innovative image processing algorithm will automatically combine multi-aperture and multi-platform sensor data onto a common time-based 3D fire map. A prototype test sensor will be test flown to validate sensor sensitivity and INS pointing accuracy data. Fire imaging data will be processed and depicted on a time-based 3D map.The successful development and commercialization of the proposed technology will provide Incident Commanders improved time-based data for managing wildfires that threaten people and infrastructure. The end goal is to improve the efficiency of fighting wildfires. Damage costs will be reduced and lives will be saved by improving the situational awareness of firefighting personnel and the general public.
Animal Health Component
40%
Research Effort Categories
Basic
10%
Applied
40%
Developmental
50%
Goals / Objectives
Project Title: Airborne Wildfire Mapping Utilizing An Array Of Thermal Infrared Cameras And Automated Multi-Aperture/Multi-Platform Fire Map ProcessingGoals:o Design, manufacture and evaluate through flight test a small, un-stabilized airborne wildfire mapping concept demonstration sensor (Reference WBS Element 1)o Design and demonstrate an innovative image processing algorithm that will automate fire mapping and automatically combine multi-aperture and multi-platform sensor data onto a common time-based 3D fire map. (Reference WBS Element 2)oDevelop Framework for Sensor/Platform Interoperability, including NIROPS and satellite platforms. (Reference WBS Element 3)o Develop a Phase II design concept for a small, low cost and lightweight multi-aperture sensor package and associated direct to map processing that can be deployed on any airborne asset, to include future USFS Unmanned Air Systems (UAS), with minimal aircraft modifications. (Reference WBS Element 4)
Project Methods
1 TIR CAMERA CORE SENSITIVITY AND INS ACCURACY TESTING: This task supports Objective #1 - TIR and INS sensor suitability for the fire mapping mission. An additional set of sensors will populate a lab integration unit to complement Trident Sensing's flying demonstrator. The lab integration unit will use 3D printed parts and serve as a hardware integration and software development unit. It will be populated with the second ship set of sensors. During flight test, the lab unit components will serve as spares for the flight test sensor. The flight test sensor contains 2 overlapping TIR camera cores, 1 Color/NIR camera core, INS/WAAS GPS and supporting processors and memory. The SBIR Phase I effort will pick-up with Trident Sensing's IR&D effort at the flight test phase and will concentrate on obtaining scientific data.1.1 TEST SENSOR DESIGN: This task captures all HW and SW efforts to develop the flight test camera system. This effort was completed under Company IR&D.1.1.1 MECHANICAL: The mechanical design task encompasses all design and manufacturing of the flight test sensor suite including aircraft mounting scheme. This effort was completed under Company IR&D.1.1.1.1 This task also supports creation of a lab "brass board" unit for HW/SW integration activities.1.1.2 ELECTRICAL: Develop system interface specification and complete all electrical interconnects required for system functionality.1.1.3 SOFTWARE: The SW development task encompasses all design and coding of software to support the flight test sensor camera control and data capture using the Python object oriented language.1.2 FUNCTIONAL TEST: Testing will be performed by the PI, SW lead and technician to verify test unit functionality. The test will be supported by functional leads on an as needed basis.1.2.1 CALIBRATION: Measure each camera core alignment relative to INS frame of reference for SW geo-referencing corrections. Generate corrections for flat field distortions.1.2.2 LAB TEST: Verify sensor control in lab environment. Capture attitude, position and camera imagery data.1.2.3 AIRCRAFT INSTALL: Install flight test sensor on aircraft.1.2.4 AIRCRAFT GROUND TEST: Verify full functionality as installed on aircraft in ground test environment. Perform safety of flight EMI/EMC source victim testing. Verify safe electrical loads. Provide flight test readiness review recommendation.1.3 FLIGHT TEST: This activity will quantity the TIR sensor sensitivity and INS accuracy as well as gather data for the fire detection algorithm validation. The test will be flown by a consultant chief pilot utilizing a leased general aviation aircraft. 20 flight hours are budgeted to this task. The PI will coordinate the ground test crew activities to include laying out the IR test target grid and tending the test targets during the overflights.1.3.1 IR TEST TARGET BORROW OR BUILD: This task encompasses the effort to obtain or build four IR test targets from 0.0156 M2 to 1 M2. IR targets will be similar to a charcoal briquette barbeque grills but with a controlled footprint. This task will be performed by a technician.1.3.2 FLT #1: FUNCTIONAL CHECK FLIGHT: Flight #1 will verify flight test sensor operation using IR target Scenario #1.1.3.3 FLT #2-5 TIR SENSITIVITY /IMU ACCURACY: Flight #2-#6 will gather TIR camera sensitivity and INS accuracy data in straight and level and maneuvering flight at multiple altitudes.1.3.4 FLT#6-7: B/U OR LIVE FIRE TEST: Flights #6 & #7 are back-up flights. If not needed as a back-up to Task 1.3.3, the flight test aircraft will be flown over a local wildfire to obtain real world fire mapping data. It is preferable to overfly a fire that has recently been mapped by the USFS PHOENIX fire sensor for comparison purposes.1.3.5 UAS DEMONSTRATION: Mechanical and electrical integration of sensor to representative multi-rotor UAS. Fly two test flights on IR targets to gather test data and UAS lessons learned for Phase II design.1.4 DATA ANALYSIS DATA ANALYSIS: Quantify TIR camera sensitivity and INS accuracy from flight test data. Qualitatively evaluate sensors for blooming, smear, jitter etc.1.4.1TIR IMAGERY SENSITIVITY: Calculate NADIR/slant detection ranges for the various IR targets.1.4.2 INS ACCURACY: Calculate IR target location from INS pointing and GPS position data. Compare to surveyed IR location and calculate pointing accuracy in straight and level and maneuvering flight.2 AUTOMATIC FIRE DETECTION ALGORITHM: This task supports Objective #2 - Implement automatic fire detection and mapping algorithms for processing fire data and registering the data to a common multi-platform 3D reference frame. This task will be conducted by the PI and commence at project kick-off. All image processing will be conducted off line using a high level scientific/mathematical programming environment such as MATLAB. Some minimal SW support is programmed for this effort.2.1 ALGORITHM DEVELOPMENT: Develop multi-camera and multi-platform image processing algorithm that will combine multiple camera images.2.2 MATLAB IMPLEMENTATION: Implement data processing algorithm coded in MATLAB.2.3 EVALUATION ON FLIGHT TEST DATA: Test data processing algorithm using actual flight test data offline in MATLAB. Combine multiple camera images into a single time based 3D image frame. Evaluate fire map data playback using 3D GIS platform such as GeoCollaborate, ARCGIS, Google Earth or Avenza.3 INTEROPERABILITY WITH SATELLITES/NIROPS DATE: This task investigates how to incorporate existing sensors and platform imaging data into the common time-based 3D fire map. A representative platform/sensor will be selected and data sharing quality metrics will be assigned. Real world data will be incorporated into the 3D fire map. Ideally this will be NIROPS or satellite mission data coinciding with the live fire flight test missions in Task 1.3.4.3.1 SELECT PLATFORM/SENSORS: Select a platform and sensor. Assign quality metrics based on thermal capability and spatial resolution.3.2 IMPLEMENT IN MATLAB: Incorporate data into MATLAB fire map processing code and overlay on the common map.4 PHASE II SYSTEM DESIGN CONCEPT: Perform high-level prototype sensor design using lessons learned from Phase I. This effort will feed into the Phase II proposal effort.4.1 MECHANICAL: Utilize Phase I lessons learned for compact prototype mechanical packaging4.2 ELECTRICAL: Utilize Phase I lessons learned for prototype electrical design. Determine if custom boards or carrier cards will be required in the prototype sensor.4.3 SOFTWARE: Utilize Phase I lessons learned to architect prototype software package.4.4 MAP PROCESSING ALGORITHM: Utilize Phase I lessons learned to propose enhancements to the map algorithm.5 TECHNICAL REPORT: PI authors technical report documenting Phase I work, results, conclusions and recommendations.