Paper Citation Record · LEDGER

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery

As of 18 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2505.00924.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.00924 v1

Coverage vector

measured 43 of 43 reference resolution

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measured 44 of 44 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T14:32:23.233221Z

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A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation d1f95656-0377-4123-80ac-e8e4caf5a8a2 · outbound

This paper cites The true role of ac- celerometer feedback in quadrotor control.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery The true role of ac- celerometer feedback in quadrotor control

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:36.152545Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1b30ccb0-dc8f-417d-99a2-3f8f21acfccc · outbound

This paper cites Influence of acoustic noise on the dynamic performance of mems gyroscopes.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Influence of acoustic noise on the dynamic performance of mems gyroscopes

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:36.111813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ae5b1c85-fc3d-490e-8375-2c5a31383766 · outbound

This paper cites Rocking drones with intentional sound noise on gyroscopic sensors.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Rocking drones with intentional sound noise on gyroscopic sensors

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:36.097575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c97280c1-fe5b-43f9-ba2b-845bbdfc87e6 · outbound

This paper cites A systematic study of physical sensor attack hardness.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery A systematic study of physical sensor attack hardness

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:36.043937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 512b7aaa-6bda-486e-b304-0cde0ab3ef69 · outbound

This paper cites In- jected and delivered: Fabricating implicit control over actuation systems by spoofing inertial sensors.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery In- jected and delivered: Fabricating implicit control over actuation systems by spoofing inertial sensors

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.946668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b453bb9b-117c-44ae-8b63-54616bfda0fb · outbound

This paper cites Ghost talk: Mitigating emi signal injection attacks against analog sensors.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Ghost talk: Mitigating emi signal injection attacks against analog sensors

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.932538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4ed5073-8c3e-4ff3-ba0c-b5b73a057b72 · outbound

This paper cites Suscep- tibility of electronic systems to high-power microwaves: Summary of test experience.IEEE Trans.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Suscep- tibility of electronic systems to high-power microwaves: Summary of test experience.IEEE Trans

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.918820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 527e1d42-2921-4de6-b17c-21c3016e1025 · outbound

This paper cites Paralyzing drones via emi signal injection on sensory communication channels.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Paralyzing drones via emi signal injection on sensory communication channels

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.804676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cb763bd4-a4d0-4564-8998-17683f878912 · outbound

This paper cites Flight recovery of mavs with compro- mised imu.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Flight recovery of mavs with compro- mised imu

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.673270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 55daca44-f06b-4120-80f2-0bf464c7e412 · outbound

This paper cites Software-based realtime re- covery from sensor attacks on robotic vehicles.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Software-based realtime re- covery from sensor attacks on robotic vehicles

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.659232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 747f8710-b237-4686-8f30-09cdc8d6ae00 · outbound

This paper cites Learn-to-recover: Retrofitting uavs with reinforcement learning-assisted flight control under cyber-physical at- tacks.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Learn-to-recover: Retrofitting uavs with reinforcement learning-assisted flight control under cyber-physical at- tacks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.612577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fe74ea88-4e3a-4701-8241-0c2509d8d226 · outbound

This paper cites Real-time attack-recovery for cyber-physical systems using linear approximations.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Real-time attack-recovery for cyber-physical systems using linear approximations

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.545974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 81eb1314-3ced-4ffc-a17d-8e337cc5c9c7 · outbound

This paper cites Recovery-by-learning: Restor- ing autonomous cyber-physical systems from sensor at- tacks.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Recovery-by-learning: Restor- ing autonomous cyber-physical systems from sensor at- tacks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.533477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fda5c67d-05bf-4bd8-ad3e-f70cb7db721c · outbound

This paper cites Un-rocking drones: Foundations of acoustic injection attacks and 14 recovery thereof.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Un-rocking drones: Foundations of acoustic injection attacks and 14 recovery thereof

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.434524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 96f14ef2-3051-46af-a993-a3e8bea2a4db · outbound

This paper cites Emc-aware design on a microcontroller for automotive applications.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Emc-aware design on a microcontroller for automotive applications

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.349561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d47527f4-2141-4b64-8868-3e7646417be0 · outbound

This paper cites Emi shielding: Meth- ods and materials—a review.Journal of applied polymer science, 112(4):2073–2086, 2009.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Emi shielding: Meth- ods and materials—a review.Journal of applied polymer science, 112(4):2073–2086, 2009

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.270008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b90df179-556a-488c-b27c-3c61f736af67 · outbound

This paper cites Low-cost imu data denoising using savitzky- golay filters.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Low-cost imu data denoising using savitzky- golay filters

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.254237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4151fcb6-0ceb-4c28-a3be-d95a7eb73874 · outbound

This paper cites Mahindrakar, Vi- tor Campagnolo Guizilini, Marco Henrique Terra, and Samrat L.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Mahindrakar, Vi- tor Campagnolo Guizilini, Marco Henrique Terra, and Samrat L

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.236152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 92148f36-1ac8-4b92-975d-59847da1ac01 · outbound

This paper cites Jamil Asghar, and Adil Sarwar.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Jamil Asghar, and Adil Sarwar

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.111778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 25706f5d-ee2e-4192-9a7f-7887f38722b5 · outbound

This paper cites An anomaly detection tech- nique based on a chi-square statistic for detecting intru- sions into information systems.Quality and Reliability Eng.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery An anomaly detection tech- nique based on a chi-square statistic for detecting intru- sions into information systems.Quality and Reliability Eng

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.056529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3e5d44c3-c1e8-419f-8bd8-788c2b11cd21 · outbound

This paper cites Savior: Secur- ing autonomous vehicles with robust physical invariants.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Savior: Secur- ing autonomous vehicles with robust physical invariants

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.040548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 49ae3406-7b1b-469c-a272-9b91f39289eb · outbound

This paper cites Px4: A node-based multithreaded open source robotics framework for deeply embedded platforms.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Px4: A node-based multithreaded open source robotics framework for deeply embedded platforms

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:35.026155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e465489f-810a-41ee-b7eb-2b9868543dd6 · outbound

This paper cites Px4 official website.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Px4 official website

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.942409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2e24b7fa-6ce4-44b5-87a9-3f3527d023d5 · outbound

This paper cites Quadcopter flight dynamics.International journal of scientific & technology research, 3(8):130– 135, 2014.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Quadcopter flight dynamics.International journal of scientific & technology research, 3(8):130– 135, 2014

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.847790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4d850195-ebec-41b9-bbf6-eb989a50e35c · outbound

This paper cites Strapdown inertial navigation integra- tion algorithm design part 1: Attitude algorithms.Jour- nal of guidance, control, and dynamics, 21(1):19–28, 1998.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Strapdown inertial navigation integra- tion algorithm design part 1: Attitude algorithms.Jour- nal of guidance, control, and dynamics, 21(1):19–28, 1998

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.833649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4c5b8796-ec73-4f27-ba0b-dc09d353ba8a · outbound

This paper cites Strapdown inertial navigation integra- tion algorithm design part 2: Velocity and position al- gorithms.Journal of Guidance, Control, and dynamics, 21(2):208–221, 1998.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Strapdown inertial navigation integra- tion algorithm design part 2: Velocity and position al- gorithms.Journal of Guidance, Control, and dynamics, 21(2):208–221, 1998

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.821206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13d9195a-59f6-440b-939d-9213f26b177d · outbound

This paper cites Sok: Rethinking sensor spoofing attacks against robotic vehicles from a systematic view.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Sok: Rethinking sensor spoofing attacks against robotic vehicles from a systematic view

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.755697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7354fe7e-7947-4336-9f0c-305b71089a0c · outbound

This paper cites A survey of unmanned aerial vehicle flight data anomaly detection: Technologies, applica- tions, and future directions.Science China Technologi- cal Sciences, 66(4):901–919, 2023.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery A survey of unmanned aerial vehicle flight data anomaly detection: Technologies, applica- tions, and future directions.Science China Technologi- cal Sciences, 66(4):901–919, 2023

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.563147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 88b4b0fa-1519-4c9c-b351-5b5c9b9f2139 · outbound

This paper cites Mul- tisensor data-fusion-based approach to airspeed mea- surement fault detection for unmanned aerial vehicles.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Mul- tisensor data-fusion-based approach to airspeed mea- surement fault detection for unmanned aerial vehicles

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.549283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7cbcc4e5-b706-40bf-812c-6ba7d9f4ee89 · outbound

This paper cites Bias compensation estimation in multi-uav formation and anomaly detection.J.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Bias compensation estimation in multi-uav formation and anomaly detection.J

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.494937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f4e27ff5-c688-427e-b7bd-2bf857951232 · outbound

This paper cites A novel online data-driven algo- rithm for detecting uav navigation sensor faults.Sensors, 17(10):2243, 2017.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery A novel online data-driven algo- rithm for detecting uav navigation sensor faults.Sensors, 17(10):2243, 2017

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.351561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 37dae272-1834-4c98-bafc-80a9e4f7323f · outbound

This paper cites Jovanov and M.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Jovanov and M

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.283005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c985434d-3659-4013-937b-2d20ffe497ca · outbound

This paper cites Anal- ysis and design of stealthy cyber attacks on unmanned aerial systems.Journal of Aerospace Information Sys- tems, 11(8):525–539, 2014.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Anal- ysis and design of stealthy cyber attacks on unmanned aerial systems.Journal of Aerospace Information Sys- tems, 11(8):525–539, 2014

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.263031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c793d4f2-9cb4-412b-bc0b-1a42744a7265 · outbound

This paper cites Detecting cyber attacks in industrial control systems using convolutional neural networks.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Detecting cyber attacks in industrial control systems using convolutional neural networks

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.248498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 08275f91-6128-4749-b4e6-ee33e421ef32 · outbound

This paper cites https://github.com/amov-lab/Prometheus.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery https://github.com/amov-lab/Prometheus

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.234000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2afd97fa-0505-44be-a0d4-be1cdc146c92 · outbound

This paper cites How the integral operations in ins algorithms overshadow the contribu- tions of imu signal denoising using low-pass filters.The Journal of Navigation, 66(6):837–858, 2013.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery How the integral operations in ins algorithms overshadow the contribu- tions of imu signal denoising using low-pass filters.The Journal of Navigation, 66(6):837–858, 2013

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.221072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4004295c-b756-43b8-b1a3-6ec2dc8eedef · outbound

This paper cites https://sites.google.com/ view/mars-uav-recovery/home.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery https://sites.google.com/ view/mars-uav-recovery/home

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.205390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b2354923-aa9b-43fe-a90b-01a6c2f0ba2b · outbound

This paper cites Almost sure stability of nonlinear systems under random and impulsive sequential attacks.IEEE Trans- actions on Automatic Control, 65(9):3879–3886, 2020.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Almost sure stability of nonlinear systems under random and impulsive sequential attacks.IEEE Trans- actions on Automatic Control, 65(9):3879–3886, 2020

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.189760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7f0c5d1d-c4df-45bd-9b80-1cb4bfc87e9d · outbound

This paper cites an unresolved cited work.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:38:34.146119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf230351-8176-4023-b7a6-9a66b0393771 · outbound

This paper cites an unresolved cited work.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:38:34.058763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 393e8836-2c70-4d6a-b076-84addafeda56 · outbound

This paper cites Preparing for the Unknown: Learning a Universal Policy with Online System Identification.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery Preparing for the Unknown: Learning a Universal Policy with Online System Identification

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T04:38:33.926857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68e0afce-7037-4abd-a8a3-36df853e4a4d · outbound

This paper cites A comparative study of nonlinear mpc and differential-flatness-based control for quadrotor agile flight.IEEE Transactions on Robotics, 38(6):3357–3373, 2022.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery A comparative study of nonlinear mpc and differential-flatness-based control for quadrotor agile flight.IEEE Transactions on Robotics, 38(6):3357–3373, 2022

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.036428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 58bb3e8a-7e1a-4133-b517-4d8c9f645019 · outbound

This paper cites https://invensense.

MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery https://invensense

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:38:34.016536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation d2ee1b0e-faf4-41b0-a55f-dbc7242f5d18 · inbound

Banshee: Target Switch Attacks on Gimbal-Stabilized Visual Tracking Systems via Acoustic Injection cites this paper.

Banshee: Target Switch Attacks on Gimbal-Stabilized Visual Tracking Systems via Acoustic Injection MARS: Defending Unmanned Aerial Vehicles From Attacks on Inertial Sensors with Model-based Anomaly Detection and Recovery

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-14T14:32:23.233221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.