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# Source Registry
## Source #1
- **Title**: Visual Odometry in GPS-Denied Zones for Fixed-Wing UAV with Reduced Accumulative Error Based on Satellite Imagery
- **Link**: https://www.mdpi.com/2076-3417/14/16/7420
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: Currently valid
- **Target Audience**: UAV visual localization researchers/implementers
- **Research Boundary Match**: Full match
- **Summary**: Demonstrates fixed-wing high-altitude monocular VO corrected by satellite imagery; highlights scale ambiguity and accumulated drift.
- **Related Sub-question**: Architecture / drift bounding
## Source #2
- **Title**: Visual place recognition for aerial imagery: A survey
- **Link**: https://arxiv.org/abs/2406.00885
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: Currently valid
- **Target Audience**: Aerial VPR researchers/implementers
- **Research Boundary Match**: Full match
- **Summary**: Reviews aerial VPR, retrieval/re-ranking, overlap/scale effects, memory/runtime issues, and georeference recall.
- **Related Sub-question**: VPR / validation
## Source #3
- **Title**: OpenVINS documentation
- **Link**: https://docs.openvins.com/
- **Tier**: L1
- **Publication Date**: 2023 latest noted release
- **Timeliness Status**: Needs verification before implementation
- **Target Audience**: VIO researchers/implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: OpenVINS is an EKF/MSCKF visual-inertial estimator supporting monocular tracking, calibration, evaluation, and covariance-aware estimation; GPL-3 license.
- **Related Sub-question**: VO/VIO
## Source #4
- **Title**: ORB-SLAM3 README
- **Link**: https://raw.githubusercontent.com/UZ-SLAMLab/ORB_SLAM3/master/README.md
- **Tier**: L1
- **Publication Date**: 2021 README, still repository source
- **Timeliness Status**: Needs verification before implementation
- **Target Audience**: SLAM implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: ORB-SLAM3 supports monocular visual-inertial SLAM and multi-map operation, requires calibration, and is GPLv3.
- **Related Sub-question**: VO/VIO alternatives
## Source #5
- **Title**: OpenCV 4.x documentation via Context7
- **Link**: https://docs.opencv.org/4.x/
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Computer vision implementers
- **Research Boundary Match**: Full match for utility layer
- **Summary**: Documents camera calibration, undistortion, and `findHomography` with RANSAC for robust geometry.
- **Related Sub-question**: Calibration / geometry
## Source #6
- **Title**: LightGlue README and Context7 docs
- **Link**: https://raw.githubusercontent.com/cvg/LightGlue/main/README.md
- **Tier**: L1
- **Publication Date**: Current repository, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Feature-matching implementers
- **Research Boundary Match**: Full match for local matching
- **Summary**: LightGlue accepts local keypoints/descriptors and returns matched coordinates/scores; supports SuperPoint, DISK, ALIKED, SIFT, adaptive pruning, CUDA, and Apache-2 for code/weights while SuperPoint has restrictive licensing.
- **Related Sub-question**: Local matching
## Source #7
- **Title**: AnyLoc README
- **Link**: https://github.com/AnyLoc/AnyLoc
- **Tier**: L1
- **Publication Date**: 2023 repository, accessed 2026-05-01
- **Timeliness Status**: Needs profiling verification
- **Target Audience**: VPR implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Provides DINOv2 + VLAD API examples and notes substantial storage/compute requirements for full experiments.
- **Related Sub-question**: VPR descriptors
## Source #8
- **Title**: DINOv2 repository
- **Link**: https://github.com/facebookresearch/dinov2
- **Tier**: L1
- **Publication Date**: 2023 repository, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Vision model implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Meta's DINOv2 implementation and models, Apache-2.0 / CC-BY-4.0 license notices.
- **Related Sub-question**: VPR descriptors
## Source #9
- **Title**: FAISS documentation and Context7 docs
- **Link**: https://faiss.ai/index.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Vector search implementers
- **Research Boundary Match**: Full match
- **Summary**: FAISS supports dense vector search, top-k retrieval, CPU/GPU indexes, product quantization, and save/load APIs; GPU indexes must be converted to CPU before saving.
- **Related Sub-question**: Descriptor retrieval
## Source #10
- **Title**: MAVSDK documentation via Context7
- **Link**: https://github.com/mavlink/mavsdk
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: MAVLink application implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: MAVSDK provides telemetry APIs including raw GPS, GPS info, status text, position/velocity, and odometry subscriptions; `GPS_INPUT` emission should use raw MAVLink/pymavlink for this project.
- **Related Sub-question**: MAVLink integration
## Source #11
- **Title**: ArduPilot MAVProxy GPSInput
- **Link**: https://ardupilot.org/mavproxy/docs/modules/GPSInput.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: ArduPilot integrators
- **Research Boundary Match**: Full match
- **Summary**: External GPS input requires `GPS1_TYPE=14` and accepts MAVLink `GPS_INPUT` fields including WGS84 lat/lon, velocity, fix type, and accuracy.
- **Related Sub-question**: MAVLink output
## Source #12
- **Title**: MAVLink common message spec: GPS_INPUT
- **Link**: https://mavlink.io/en/messages/common.html#GPS_INPUT
- **Tier**: L1
- **Publication Date**: Current spec, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: MAVLink implementers
- **Research Boundary Match**: Full match
- **Summary**: Defines `GPS_INPUT` fields, fix type semantics, `horiz_accuracy`, and ignore flags.
- **Related Sub-question**: MAVLink output / confidence
## Source #13
- **Title**: ArduPilot GPS failsafe and glitch protection
- **Link**: https://ardupilot.org/copter/docs/gps-failsafe-glitch-protection.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Reference only for Plane
- **Target Audience**: ArduPilot operators
- **Research Boundary Match**: Partial overlap
- **Summary**: Documents GPS glitch protection and notes inertial-only position degrades quickly; Copter-specific defaults must not be assumed for Plane.
- **Related Sub-question**: Failsafe / spoofing
## Source #14
- **Title**: ArduPilot EKF failsafe
- **Link**: https://ardupilot.org/copter/docs/ekf-inav-failsafe.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Reference only for Plane
- **Target Audience**: ArduPilot operators
- **Research Boundary Match**: Partial overlap
- **Summary**: Explains EKF variance failsafe behavior and why spoof/glitch tests must be parameterized.
- **Related Sub-question**: Failsafe / spoofing
## Source #15
- **Title**: Jetson Orin Nano Super Developer Kit
- **Link**: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/nano-super-developer-kit/
- **Tier**: L1
- **Publication Date**: Current page, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Embedded AI implementers
- **Research Boundary Match**: Full match
- **Summary**: Confirms 67 INT8 TOPS, 8 GB LPDDR5, 102 GB/s, and 7-25 W power range.
- **Related Sub-question**: Runtime
## Source #16
- **Title**: NVIDIA JetPack 6.2 Super Mode blog
- **Link**: https://developer.nvidia.com/blog/nvidia-jetpack-6-2-brings-super-mode-to-nvidia-jetson-orin-nano-and-jetson-orin-nx-modules/
- **Tier**: L2
- **Publication Date**: 2024
- **Timeliness Status**: Currently valid
- **Target Audience**: Jetson developers
- **Research Boundary Match**: Full match
- **Summary**: Explains 25 W and MAXN Super modes and warns thermal design must accommodate the new power modes or throttling occurs.
- **Related Sub-question**: Runtime / thermal
## Source #17
- **Title**: PMTiles Concepts
- **Link**: https://docs.protomaps.com/pmtiles/
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Geospatial storage implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: PMTiles is single-file tiled archive, efficient for reads, but read-only and not update-in-place.
- **Related Sub-question**: Cache storage
## Source #18
- **Title**: GDAL COG driver
- **Link**: https://gdal.org/en/stable/drivers/raster/cog.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Geospatial raster implementers
- **Research Boundary Match**: Full match
- **Summary**: Defines COG creation options for tiled, compressed, overview-enabled GeoTIFFs.
- **Related Sub-question**: Cache storage
## Source #19
- **Title**: AerialVL dataset
- **Link**: https://github.com/hmf21/AerialVL
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: Currently valid
- **Target Audience**: Aerial visual localization researchers
- **Research Boundary Match**: Partial overlap
- **Summary**: Public aerial localization benchmark with UAV sequences, reference maps, and geo-referenced evaluation data.
- **Related Sub-question**: Validation
## Source #20
- **Title**: EuRoC MAV Dataset
- **Link**: http://projects.asl.ethz.ch/datasets/euroc-mav/
- **Tier**: L1
- **Publication Date**: 2016
- **Timeliness Status**: Stable benchmark
- **Target Audience**: VIO researchers
- **Research Boundary Match**: Partial overlap
- **Summary**: Stereo camera + IMU + ground truth benchmark useful for VIO sanity tests but not representative of high-altitude nadir fixed-wing imagery.
- **Related Sub-question**: Validation
## Source #21
- **Title**: NVIDIA/TensorRT issue: DINOv2 TensorRT performance/precision on Jetson
- **Link**: https://github.com/NVIDIA/TensorRT/issues/4348
- **Tier**: L4
- **Publication Date**: 2024
- **Timeliness Status**: Needs verification
- **Target Audience**: Jetson/TensorRT implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Reports limited mixed-precision gains for DINOv2-S on Jetson/RTX, suggesting DINOv2 optimization is not automatically beneficial.
- **Related Sub-question**: Mode B performance risk
## Source #22
- **Title**: NVIDIA Developer Forum: DINOv2 TensorRT model performance issue
- **Link**: https://forums.developer.nvidia.com/t/dinov2-tensorrt-model-performance-issue/312251
- **Tier**: L4
- **Publication Date**: 2024
- **Timeliness Status**: Needs verification
- **Target Audience**: Jetson/TensorRT implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Reports DINOv2 embedding distance changes after TensorRT conversion on Jetson Orin Nano; requires embedding-fidelity validation before relying on TensorRT descriptors.
- **Related Sub-question**: Mode B performance/quality risk
## Source #23
- **Title**: LightGlue license issue discussions
- **Link**: https://github.com/cvg/LightGlue/issues/120
- **Tier**: L4
- **Publication Date**: 2024
- **Timeliness Status**: Currently relevant
- **Target Audience**: Feature-matching implementers
- **Research Boundary Match**: Full match for licensing
- **Summary**: Community discussion highlights restrictive SuperPoint licensing inside the LightGlue ecosystem and supports avoiding SuperPoint as default production extractor.
- **Related Sub-question**: Mode B licensing risk
## Source #24
- **Title**: ArduPilot issue: GPS_INPUT velocity ignore flag pitfall
- **Link**: https://github.com/ArduPilot/ardupilot/issues/19633
- **Tier**: L4
- **Publication Date**: 2021
- **Timeliness Status**: Needs SITL verification
- **Target Audience**: ArduPilot integrators
- **Research Boundary Match**: Full match for GPS_INPUT caution
- **Summary**: Reports EKF3 may use zero velocity when `GPS_INPUT_IGNORE_FLAG_VEL_HORIZ` is set, so velocity-source parameters must be tested rather than relying only on ignore flags.
- **Related Sub-question**: Mode B MAVLink pitfall
## Source #25
- **Title**: FAISS install documentation
- **Link**: https://github.com/facebookresearch/faiss/blob/main/INSTALL.md
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Vector search implementers
- **Research Boundary Match**: Full match
- **Summary**: FAISS CPU conda package supports aarch64, while GPU package availability is x86-64 focused; Jetson design should assume CPU FAISS unless a custom build is proven.
- **Related Sub-question**: Mode B FAISS deployment
## Source #26
- **Title**: GNSS-denied geolocalization of UAVs by visual matching of onboard camera images with orthophotos
- **Link**: https://ar5iv.labs.arxiv.org/html/2103.14381
- **Tier**: L1
- **Publication Date**: 2021
- **Timeliness Status**: Stable mechanism reference
- **Target Audience**: UAV visual geolocalization researchers
- **Research Boundary Match**: Partial overlap
- **Summary**: Demonstrates visual matching with orthophotos and Monte Carlo/local planarity ideas; supports using orthorectified reference maps but does not cover all adversarial visual attacks.
- **Related Sub-question**: Mode B alternative / security limits
## Source #27
- **Title**: OpenVINS LICENSE
- **Link**: https://github.com/rpng/open_vins/blob/master/LICENSE
- **Tier**: L1
- **Publication Date**: Current repository, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: VIO implementers / product owners
- **Research Boundary Match**: Full match for licensing
- **Summary**: OpenVINS is GPLv3-licensed; this is a production dependency constraint, not a technical capability limitation.
- **Related Sub-question**: Mode B round 2 — OpenVINS vs custom production estimator
## Source #28
- **Title**: OpenVINS documentation and Context7 lookup
- **Link**: https://docs.openvins.com/index.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: VIO implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: OpenVINS is a strong EKF/MSCKF VIO system for monocular camera + IMU reference runs, with calibration and covariance-aware state estimation, but it does not own the project-specific satellite anchor, GPS_INPUT, source-label, spoofing, blackout, and cache-poisoning state machine.
- **Related Sub-question**: Mode B round 2 — OpenVINS vs custom production estimator
## Source #29
- **Title**: OpenCV 4.x calibration/homography documentation and Context7 lookup
- **Link**: https://docs.opencv.org/4.x/
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: Computer vision implementers
- **Research Boundary Match**: Full match for geometry utility layer
- **Summary**: OpenCV 4.x provides calibration, undistortion, homography estimation, RANSAC/USAC robust estimation, and reprojection-error primitives under a permissive license; it is a utility layer rather than a complete GPS-denied estimator.
- **Related Sub-question**: Mode B round 2 — custom OpenCV boundary
## Source #30
- **Title**: AnyLoc: Towards Universal Visual Place Recognition
- **Link**: https://arxiv.org/html/2308.00688
- **Tier**: L1
- **Publication Date**: 2023; ICRA 2024
- **Timeliness Status**: Currently valid, profiling required before deployment
- **Target Audience**: VPR implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: AnyLoc combines DINOv2 features with VLAD aggregation for broad VPR, including aerial data, and supports the selected DINOv2-VLAD retrieval family while leaving runtime/storage tuning as a deployment gate.
- **Related Sub-question**: Mode B round 2 — satellite retrieval
## Source #31
- **Title**: ALIKED-LightGlue-ONNX and LightGlue ONNX/TensorRT deployment reports
- **Link**: https://github.com/ikeboo/ALIKED-LightGlue-ONNX
- **Tier**: L2
- **Publication Date**: Current repository, accessed 2026-05-01
- **Timeliness Status**: Promising but needs Jetson verification
- **Target Audience**: Local feature matching implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: ONNX/optimized variants show a credible deployment path for ALIKED + LightGlue, but public evidence is not enough to assume Jetson Orin Nano p95 latency without project profiling.
- **Related Sub-question**: Mode B round 2 — local matcher deployability
## Source #32
- **Title**: Visual place recognition for aerial imagery: A survey
- **Link**: https://arxiv.org/abs/2406.00885
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: Currently valid
- **Target Audience**: Aerial VPR researchers / implementers
- **Research Boundary Match**: Full match
- **Summary**: Aerial VPR performance depends materially on tile scale, overlap, weather, repetitive patterns, and re-ranking cost; this supports overlapped VPR chunks, dynamic top-K, and conditional local verification.
- **Related Sub-question**: Mode B round 2 — satellite retrieval and anchor verification
## Source #33
- **Title**: BASALT repository and documentation
- **Link**: https://github.com/VladyslavUsenko/basalt
- **Tier**: L1
- **Publication Date**: Current repository, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: VIO implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: BASALT provides visual-inertial odometry and mapping, camera/IMU calibration tools, EuRoC/TUM VI support, and a BSD-style production-friendly licensing path.
- **Related Sub-question**: Mode B round 3 — Kimera vs BASALT vs OpenVINS
## Source #34
- **Title**: HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry
- **Link**: https://arxiv.org/pdf/2106.11857
- **Tier**: L1
- **Publication Date**: 2021
- **Timeliness Status**: Stable benchmark reference
- **Target Audience**: VIO researchers / embedded implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Reports EuRoC RMS ATE comparisons including BASALT mean about 0.051 m online stereo and Kimera mean about 0.12 m, plus notes that optimization-based methods often lack direct uncertainty quantification compared with filters.
- **Related Sub-question**: Mode B round 3 — VIO error and confidence comparison
## Source #35
- **Title**: OpenVINS issue #402 — up-to-date ATE and RTE metrics
- **Link**: https://github.com/rpng/open_vins/issues/402
- **Tier**: L4
- **Publication Date**: 2024
- **Timeliness Status**: Community benchmark, verify in our replay harness
- **Target Audience**: VIO implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Community EuRoC comparison reports BASALT average ATE about 0.072 m with 100% completion, and OpenVINS average ATE about 0.091 m with about 88.55% completion and a divergence on one hard sequence.
- **Related Sub-question**: Mode B round 3 — BASALT vs OpenVINS error/completion
## Source #36
- **Title**: Kimera-VIO mono-inertial parameter issues
- **Link**: https://github.com/MIT-SPARK/Kimera-VIO/issues/254
- **Tier**: L4
- **Publication Date**: 2024
- **Timeliness Status**: Relevant implementation caveat
- **Target Audience**: VIO implementers
- **Research Boundary Match**: Partial overlap
- **Summary**: Kimera-VIO stereo path remains strong, but mono-inertial configurations had documented poor default performance; parameter changes improved one EuRoC mono setup to less than about +/-0.2 m per axis.
- **Related Sub-question**: Mode B round 3 — Kimera mono/nadir risk
## Source #37
- **Title**: RaD-VIO and downward-facing VIO literature
- **Link**: https://arxiv.org/abs/1810.08704
- **Tier**: L1
- **Publication Date**: 2018
- **Timeliness Status**: Stable mechanism reference
- **Target Audience**: MAV downward-camera VIO researchers
- **Research Boundary Match**: Full match for nadir-camera caveat
- **Summary**: Downward-facing monocular VIO has planar-scene and observability challenges; range/altitude and IMU constraints are important when the camera sees mostly ground plane.
- **Related Sub-question**: Mode B round 3 — nadir support and limitations
## Source #38
- **Title**: OpenVINS covariance documentation and StateHelper APIs
- **Link**: https://docs.openvins.com/dev-index.html
- **Tier**: L1
- **Publication Date**: Current docs, accessed 2026-05-01
- **Timeliness Status**: Currently valid
- **Target Audience**: VIO implementers
- **Research Boundary Match**: Full match for covariance/confidence output
- **Summary**: OpenVINS maintains EKF covariance and exposes full/marginal covariance helpers, making it the strongest reference for covariance consistency even if GPLv3 blocks default production use.
- **Related Sub-question**: Mode B round 3 — confidence/covariance support
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