# Source Registry

## Source #1
- **Title**: ArduPilot AP_GPS_Params — GPS_RATE minimum 5Hz
- **Link**: https://github.com/ArduPilot/ardupilot/pull/15980
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: ArduPilot flight controller users
- **Research Boundary Match**: ✅ Full match
- **Summary**: ArduPilot enforces minimum 5Hz GPS update rate. GPS_RATE parameter description: "Lowering below 5Hz(default) is not allowed."
- **Related Sub-question**: SQ-12

## Source #2
- **Title**: MAVLink GPS_INPUT Message Definition
- **Link**: https://ardupilot.org/mavproxy/docs/modules/GPSInput.html
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: MAVLink developers
- **Research Boundary Match**: ✅ Full match
- **Summary**: GPS_INPUT requires: lat, lon, alt, fix_type, hdop, vdop, horiz_accuracy, vert_accuracy, speed_accuracy, vn, ve, vd, time_usec, time_week, time_week_ms, satellites_visible, gps_id, ignore_flags. GPS_TYPE=14 for MAVLink GPS.
- **Related Sub-question**: SQ-6, SQ-12

## Source #3
- **Title**: pymavlink GPS_INPUT example (GPS_INPUT_pymavlink.py)
- **Link**: https://webperso.ensta.fr/lebars/Share/GPS_INPUT_pymavlink.py
- **Tier**: L3
- **Publication Date**: 2024
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: pymavlink developers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Working pymavlink example sending GPS_INPUT over serial at 10Hz with GPS time calculation from system time.
- **Related Sub-question**: SQ-6

## Source #4
- **Title**: PyCuVSLAM API Reference (v15.0.0)
- **Link**: https://wiki.seeedstudio.com/pycuvslam_recomputer_robotics/
- **Tier**: L2
- **Publication Date**: 2026-03
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: cuVSLAM developers on Jetson
- **Research Boundary Match**: ✅ Full match
- **Summary**: cuVSLAM supports mono/stereo/inertial modes. Requires Camera model (fx,fy,cx,cy,distortion), ImuCalibration (noise density, random walk, frequency, T_imu_rig). Modes: Performance/Precision/Moderate. IMU fallback ~1s acceptable quality.
- **Related Sub-question**: SQ-1, SQ-5, SQ-9

## Source #5
- **Title**: ESKF Python implementation for fixed-wing UAV
- **Link**: https://github.com/ludvigls/ESKF
- **Tier**: L4
- **Publication Date**: 2023
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: ESKF implementers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Reference ESKF: 16-state vector (pos[3], vel[3], quat[4], acc_bias[3], gyro_bias[3]). Prediction with IMU at high rate. Update with GPS position/velocity. Tuning parameters: Q (process noise), R (measurement noise).
- **Related Sub-question**: SQ-2

## Source #6
- **Title**: ROS ESKF based on PX4/ecl — multi-sensor fusion
- **Link**: https://github.com/EliaTarasov/ESKF
- **Tier**: L4
- **Publication Date**: 2022
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: UAV ESKF implementers
- **Research Boundary Match**: ✅ Full match
- **Summary**: ESKF fusing GPS, Magnetometer, Vision Pose, Optical Flow, RangeFinder with IMU. Shows that vision pose and optical flow are separate measurement models, each with its own observation matrix and noise parameters.
- **Related Sub-question**: SQ-2

## Source #7
- **Title**: Visual-Inertial Odometry Scale Observability (Range-VIO)
- **Link**: https://arxiv.org/abs/2103.15215
- **Tier**: L1
- **Publication Date**: 2021
- **Timeliness Status**: ✅ Currently valid (fundamental research)
- **Target Audience**: VIO researchers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Monocular VIO cannot observe metric scale without accelerometer excitation (not constant velocity). A 1D range sensor makes scale observable. For our case, barometric altitude + known flight altitude provides this constraint.
- **Related Sub-question**: SQ-2, SQ-4

## Source #8
- **Title**: NaviLoc: Trajectory-Level Visual Localization for GNSS-Denied UAVs
- **Link**: https://www.mdpi.com/2504-446X/10/2/97
- **Tier**: L1
- **Publication Date**: 2025
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: GPS-denied UAV navigation researchers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Trajectory-level optimization fusing VPR with VIO achieves 19.5m mean error at 50-150m altitude. Key insight: treating satellite matching as noisy measurement rather than ground truth, with trajectory-level optimization. Runs at 9 FPS on RPi 5.
- **Related Sub-question**: SQ-3, SQ-13

## Source #9
- **Title**: SatLoc-Fusion: Hierarchical Adaptive Fusion Framework
- **Link**: https://www.scilit.com/publications/e5cafaf875a49297a62b298a89d5572f
- **Tier**: L1
- **Publication Date**: 2025
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: GPS-denied UAV researchers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Three-layer fusion: absolute geo-localization (DinoV2), relative VO (XFeat), optical flow velocity. Adaptive weighting based on confidence. Achieves <15m error, >90% trajectory coverage. 2Hz on 6 TFLOPS edge.
- **Related Sub-question**: SQ-3, SQ-10, SQ-13

## Source #10
- **Title**: Auterion GPS-Denied Workflow
- **Link**: https://docs.auterion.com/vehicle-operation/auterion-mission-control/useful-resources/operations/gps-denied-workflow
- **Tier**: L2
- **Publication Date**: 2025
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: UAV operators
- **Research Boundary Match**: ⚠️ Partial overlap (multirotor focus, but procedures applicable)
- **Summary**: Pre-flight: manually set home position, reset heading/position, configure wind. In-flight: enable INS mode. Defines operational procedures for GPS-denied missions.
- **Related Sub-question**: SQ-15

## Source #11
- **Title**: PX4 GNSS-Degraded & Denied Flight (Dead-Reckoning)
- **Link**: https://docs.px4.io/main/en/advanced_config/gnss_degraded_or_denied_flight.html
- **Tier**: L1
- **Publication Date**: 2025
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: PX4 users
- **Research Boundary Match**: ⚠️ Partial overlap (PX4-specific, but concepts apply to ArduPilot)
- **Summary**: GPS-denied requires redundant position/velocity sensors. Dead-reckoning mode for intermittent GNSS loss. Defines failsafe behaviors when GPS is lost.
- **Related Sub-question**: SQ-15

## Source #12
- **Title**: Google Maps Ukraine satellite imagery coverage
- **Link**: https://newsukraine.rbc.ua/news/google-maps-has-surprise-for-satellite-imagery-1727182380.html
- **Tier**: L3
- **Publication Date**: 2024-09
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: General public
- **Research Boundary Match**: ✅ Full match
- **Summary**: Google Maps improved imagery quality with Cloud Score+ AI. However, conflict zone imagery is intentionally older (>1 year). Ukrainian officials flagged security concerns about imagery revealing military positions.
- **Related Sub-question**: SQ-10

## Source #13
- **Title**: Jetson Orin Nano Super thermal behavior at 25W
- **Link**: https://edgeaistack.app/blog/jetson-orin-nano-power-consumption/
- **Tier**: L3
- **Publication Date**: 2025
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: Jetson developers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Thermal throttling at SoC junction >80°C. Sustained GPU at 25W: ~50-51°C reported. Active cooling required for >15W. Most production workloads 8-15W.
- **Related Sub-question**: SQ-11

## Source #14
- **Title**: Automated Image Matching for Satellite Images with Different GSDs
- **Link**: https://www.kjrs.org/journal/view.html?pn=related&uid=756&vmd=Full
- **Tier**: L1
- **Publication Date**: 2024
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: Remote sensing researchers
- **Research Boundary Match**: ✅ Full match
- **Summary**: GSD mismatch between satellite and aerial images requires scale normalization via subsampling/super-resolution. Coarse-to-fine matching strategy effective. Scale-invariant features (SIFT, deep features) partially handle scale differences.
- **Related Sub-question**: SQ-7

## Source #15
- **Title**: Optimized VO and satellite image matching for UAVs (Istanbul Tech thesis)
- **Link**: https://polen.itu.edu.tr/items/1fe1e872-7cea-44d8-a8de-339e4587bee6
- **Tier**: L1
- **Publication Date**: 2025
- **Timeliness Status**: ✅ Currently valid
- **Target Audience**: GPS-denied UAV researchers
- **Research Boundary Match**: ✅ Full match
- **Summary**: Complete VO+satellite matching pipeline. Coordinate transforms: GPS → local NED for trajectory comparison. PnP solver for UAV pose from correspondences. Map retrieval using VO-estimated position to crop satellite tiles.
- **Related Sub-question**: SQ-4, SQ-5
