The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Unmanned Aircraft Capture and Control Via GPS Spoofing
Abstract
The theory and practice of unmanned aerial vehicle (UAV) capture and control via Global Positioning System (GPS) signal spoofing are analyzed and demonstrated. The goal of this work is to explore UAV vulnerability to deceptive GPS signals. Specifically, this paper (1) establishes the necessary conditions for UAV capture via GPS spoofing, and (2) explores the spoofer's range of possible post‐capture control over the UAV. A UAV is considered captured when a spoofer gains the ability to eventually specify the UAV's position and velocity estimates. During post‐capture control, the spoofer manipulates the true state of the UAV, potentially resulting in the UAV flying far from its flight plan without raising alarms. Both overt and covert spoofing strategies are considered, as distinguished by the spoofer's attempts to evade detection by the target GPS receiver and by the target navigation system's state estimator, which is presumed to have access to non‐GPS navigation sensor data. GPS receiver tracking loops are analyzed and tested to assess the spoofer's capability for covert capture of a mobile target. The coupled dynamics of a UAV and spoofer are analyzed and simulated to explore practical post‐capture control scenarios. A field test demonstrates capture and rudimentary control of a rotorcraft UAV, which results in unrecoverable navigation errors that cause the UAV to crash.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software
Bar‐Shalom, Y., Li, X. ‐., & Kirubarajan, T. (2002) · doi:10.1002/0471221279 · Cited by 6,782
Simultaneous localization and mapping: part I
Durrant-Whyte, H., & Bailey, T. (2006) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2006.1638022 · Cited by 4,199
Global positioning system : theory and applications
Parkinson, B. W., & Spilker, J. J. (1996) · Cited by 2,550
Nonlinear controllability and observability
Hermann, R., & Krener, A. (1977) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1977.1101601 · Cited by 2,374 · cited 1×
“One can think of the capture condition as analogous to nonlinear controllability of the PV estimator in steady state (Hermann and Krener, 1977): from an initial estimate ˆ x ( t 0 ) at the onset of spoofing, there exists t 1 ≥ t 0 such that ˆ x ( t 1 ) ≈ x (cid:4) .”
BackgroundSurvey of advances in guidance, navigation, and control of unmanned rotorcraft systems
Kendoul, F. (2012) · Journal of Field Robotics · doi:10.1002/rob.20414 · Cited by 663
Assessing the Spoofing Threat: Development of a Portable GPS Civilian Spoofer
Kintner, P. M. (2018) · Texas ScholarWorks (Texas Digital Library) · doi:10.15781/t26t0hc7q · Cited by 536
On the requirements for successful GPS spoofing attacks
Tippenhauer, N. O., Pöpper, C., Rasmussen, K. B., & Capkun, S. (2011) · Proceedings of the 18th ACM conference on Computer and communications security · doi:10.1145/2046707.2046719 · Cited by 506
Monocular‐SLAM–based navigation for autonomous micro helicopters in GPS‐denied environments
Weiss, S., Scaramuzza, D., & Siegwart, R. (2011) · Journal of Field Robotics · doi:10.1002/rob.20412 · Cited by 414
Evaluation of the vulnerability of phasor measurement units to GPS spoofing attacks
Shepard, D. P., Humphreys, T. E., & Fansler, A. A. (2012) · International Journal of Critical Infrastructure Protection · doi:10.1016/j.ijcip.2012.09.003 · Cited by 316
Self-citationFusion of IMU and Vision for Absolute Scale Estimation in Monocular SLAM
Nützi, G., Weiss, S., Scaramuzza, D., & Siegwart, R. (2011) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-010-9490-z · Cited by 286
RANGE–Robust autonomous navigation in GPS‐denied environments
Bachrach, A., Prentice, S., He, R., & Roy, N. (2011) · Journal of Field Robotics · doi:10.1002/rob.20400 · Cited by 285
Who's Afraid of the Spoofer? GPS/GNSS Spoofing Detection via Automatic Gain Control (AGC)
Akos, D. M. (2012) · Navigation · doi:10.1002/navi.19 · Cited by 266
Detection Strategy for Cryptographic GNSS Anti-Spoofing
Humphreys, T. E. (2013) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2013.6494400 · Cited by 262
Self-citationGPS‐denied Indoor and Outdoor Monocular Vision Aided Navigation and Control of Unmanned Aircraft
Chowdhary, G., Johnson, E. N., Magree, D., Wu, A., & Shein, A. (2013) · Journal of Field Robotics · doi:10.1002/rob.21454 · Cited by 178
Controlled-root formulation for digital phase-locked loops
Stephens, S. A., & Thomas, J. B. (1995) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/7.366295 · Cited by 165
Modeling the Effects of Ionospheric Scintillation on GPS Carrier Phase Tracking
Humphreys, T. E., Psiaki, M. L., & Kintner, P. M., Jr. (2010) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2010.5595583 · Cited by 157
Self-citationEvaluation of Smart Grid and Civilian UAV Vulnerability to GPS Spoofing Attacks
Fansler, A. A. (2018) · Texas ScholarWorks (Texas Digital Library) · doi:10.15781/t2xw48c62 · Cited by 152
Characterization of Various IMU Error Sources and the Effect on Navigation Performance
Flenniken, W. S., Wall, J. H., & Bevly, D. M. (2005) · Cited by 107
Vision‐based terrain following for an unmanned rotorcraft
Garratt, M., & Chahl, J. (2008) · Journal of Field Robotics · doi:10.1002/rob.20239 · Cited by 79
GPS Receiver RF Interference Monitoring, Mitigation, and Analysis Techniques
Ward, P. W. (1994) · NAVIGATION Journal of the Institute of Navigation · doi:10.1002/j.2161-4296.1994.tb01886.x · Cited by 74
Civilian GPS Spoofing Detection based on DualReceiver Correlation of Military Signals
Humphreys, T. E. (2018) · doi:10.15781/t2513vc49 · Cited by 63
Self-citationWide-area augmented reality using camera tracking and mapping in multiple regions
Castle, R. O., Klein, G., & Murray, D. W. (2011) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2011.02.007 · Cited by 51
Cited by
Psiaki, M. L., & Humphreys, T. E. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2526658 · Cited by 736
Self-citationSecurity analysis of drones systems: Attacks, limitations, and recommendations
Yaacoub, J.-P., Noura, H., Salman, O., & Chehab, A. (2020) · Internet of Things · doi:10.1016/j.iot.2020.100218 · Cited by 727
A survey of physics-based attack detection in cyber-physical systems
Giraldo, J., Urbina, D., Cardenas, A., Valente, J., Faisal, M., Ruths, J., Tippenhauer, N. O., Sandberg, H., & Candell, R. (2019) · ACM Computing Surveys · doi:10.1145/3203245 · Cited by 535
Security, Privacy, and Safety Aspects of Civilian Drones: A Survey
Altawy, R., & Youssef, A. M. (2017) · ACM Transactions on Cyber-Physical Systems · doi:10.1145/3001836 · Cited by 428
Defending Airports from UAS: A Survey on Cyber-Attacks and Counter-Drone Sensing Technologies
Lykou, G., Moustakas, D., & Gritzalis, D. (2020) · Sensors · doi:10.3390/s20123537 · Cited by 268
Metadata
- Authors
- Kerns, A. J., Shepard, D. P., Bhatti, J. A., & Humphreys, T. E.
- Venue
- Journal of Field Robotics
- Publisher
- Wiley
- Published
- 2014-04-10
- Volume
- 31
- Issue
- 4
- Pages
- 617-636
- ISSN
- 1556-4959 (ISSN-L)
- 1556-4967
- OpenAlex
- W1921864689
- Cited by
- 688
- References
- 23
- FWCI
- 38.68
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
