Communication-based UAV Swarm Missions

Unmanned aerial vehicles have developed rapidly in recent years due to technological advances. UAV technology can be applied to a wide range of applications in surveillance, rescue, agriculture and transport. The problems that can exist in these areas can be mitigated by combining clusters of drones with several technologies. For example, when a swarm of drones is under attack, it may not be able to obtain the position feedback provided by the Global Positioning System (GPS). This poses a new challenge for the UAV swarm to fulfill a specific mission. This thesis intends to use as few sensors as possible on the UAVs and to design the smallest possible information transfer between the UAVs to maintain the shape of the UAV formation in flight and to follow a predetermined trajectory. This thesis presents Extended Kalman Filter methods to navigate autonomously in a GPS-denied environment. The UAV formation control and distributed communication methods are also discussed and given in detail

Detection solution analysis for simplistic spoofing attacks in commercial mini and micro UAVs

Enamus droone kasutab lennundusest pärit GPS navigatsiooniseadmeid, millel puuduvad turvaprotokollid ning nende riskioht pahatahtlike rünnakute sihtmärgina on kasvanud hüppeliselt lähimineviku arengute ja progressi tõttu SDR ja GNSS simulatsioonitarkvara valdkonnas. See on loonud ligipääsu tehnikale amatöörkasutajatele, millel on saatja aadressi võltsimise jõudlus. Need potensiaalsed rünnakud kuuluvad lihtsakoeliste kategooriasse, kuid selle uurimustöö tulemusena selgus, et nendes rünnakute edukuses on olulised erinevused teatud GPS vastuvõtjate ja konfiguratsioonide vahel. \n\rSee uurimustöö analüüsis erinevaid saatja aadressi võltsimise avastamise meetodeid, mis olid avatud kasutajatele ning valis välja need, mis on sobilikud mini- ja mikrodroonide tehnonõuetele ja operatsioonistsenaariumitele, eesmärgiga pakkuda välja GPS aadresside rünnakute avastamiseks rakenduste tasandil avatud allikakoodiga Ground Control Station tarkvara SDK. Avastuslahenduse eesmärk on jälgida ja kinnitada äkilisi, abnormaalseid või ebaloogilisi tulemväärtusi erinevates drooni sensiorites lisaallkatest pärit lisainfoga. \n\rLäbiviidud testid kinnitavad, et olenevalt olukorrast ja tingimustest saavad saatja aadressi võltsimise rünnakud õnnestuda. Rünnakud piiravad GPS mehanismide ligipääsu, mida saab kasutada rünnakute avastuseks. Neid rünnakuid puudutav info asetseb infovoos või GPSi signaalprotsessi tasandis, kuid seda infot ei saa haarata tasandile kus SDK tarkvara haldab kõigi teiste sensorite infot.Most of UAVs are GPS navigation based aircrafts that rely on a system with lack of security, their latent risk against malicious attacks has been raised with the recent progress and development in SDRs and GNSS simulation software, facilitating to amateurs the accessibility of equipment with spoofing capabilities. The attacks which can be done with this setup belong to the category simplistic, however, during this thesis work there are validated different cases of successful results under certain GPS receivers’ state or configuration.\n\rThis work analysis several spoofing detection methods found in the open literature, and selects the ones which can be suitable for mini and micro UAV technical specifications and operational scenario, for proposing a GPS spoofing detection solution developed in the application layer of an open source code Ground Control Station software SDK. The detection solution is intended to monitor and correlate abrupt, abnormal or unreasonable values of different sensors of the UAV with data obtained from available additional sources.\n\rThe conducted tests validate the cases and circumstances where the spoofing attacks were successful. Limitations include the lack of mechanisms to access GPS values which can be useful for detection spoofing attacks, but reside in the data bit or signal processing layer of the GPS and can not be retrieve to the layer where the SDK in computing all data of other sensors

The Response of Beef Cattle to Disturbances from Unmanned Aerial Vehicles (UAVs)

Unmanned aerial vehicles (UAVs) are increasingly becoming common in animal agriculture. However, research regarding the impact of UAV disturbance on animal wellbeing is lacking or limited. The goal of this study was to investigate the effect of UAV flights on beef cattle by measuring cattle heart and movement rate when introduced to single or multiple UAV flights. A total of 16 -18 crossbred beef heifers were introduced to different flights patterns at between 5 and 9 m above ground level (AGL) at approximately 1 to 2 m/s horizontal velocity for 4 weeks with flights repeated 3 days per week. Results from the study showed that single UAV flights conducted in (i) circular and (ii) grid pattern flights had no significant effect on heifer heart and movement rate. However, multiple (i) circular pattern and (ii) approach style flights increased heifer heart rate when first introduced to UAVs, but repeated flights resulted in habituation. Moreover, heifers first introduced to circular pattern flights were likely to flee but became habituated after repeated flights. However, heifers introduced to approach style flights showed more fleeing behavior even after repeated flights. The findings of this study will provide information for safely using UAVs in cattle health and behavior monitoring

POLOCALC: a Novel Method to Measure the Absolute Polarization Orientation of the Cosmic Microwave Background

We describe a novel method to measure the absolute orientation of the polarization plane of the CMB with arcsecond accuracy, enabling unprecedented measurements for cosmology and fundamental physics. Existing and planned CMB polarization instruments looking for primordial B-mode signals need an independent, experimental method for systematics control on the absolute polarization orientation. The lack of such a method limits the accuracy of the detection of inflationary gravitational waves, the constraining power on the neutrino sector through measurements of gravitational lensing of the CMB, the possibility of detecting Cosmic Birefringence, and the ability to measure primordial magnetic fields. Sky signals used for calibration and direct measurements of the detector orientation cannot provide an accuracy better than 1 deg. Self-calibration methods provide better accuracy, but may be affected by foreground signals and rely heavily on model assumptions. The POLarization Orientation CALibrator for Cosmology, POLOCALC, will dramatically improve instrumental accuracy by means of an artificial calibration source flying on balloons and aerial drones. A balloon-borne calibrator will provide far-field source for larger telescopes, while a drone will be used for tests and smaller polarimeters. POLOCALC will also allow a unique method to measure the telescopes' polarized beam. It will use microwave emitters between 40 and 150 GHz coupled to precise polarizing filters. The orientation of the source polarization plane will be registered to sky coordinates by star cameras and gyroscopes with arcsecond accuracy. This project can become a rung in the calibration ladder for the field: any existing or future CMB polarization experiment observing our polarization calibrator will enable measurements of the polarization angle for each detector with respect to absolute sky coordinates.Comment: 15 pages, 5 figures, Accepted by Journal of Astronomical Instrumentatio

Tracking the Fine Scale Movements of Fish using Autonomous Maritime Robotics: A Systematic State of the Art Review

This paper provides a systematic state of the art review on tracking the fine scale movements of fish with the use of autonomous maritime robotics. Knowledge of migration patterns and the localization of specific species of fish at a given time is vital to many aspects of conservation. This paper reviews these technologies and provides insight into what systems are being used and why. The review results show that a larger amount of complex systems that use a deep learning techniques are used over more simplistic approaches to the design. Most results found in the study involve Autonomous Underwater Vehicles, which generally require the most complex array of sensors. The results also provide insight into future research such as methods involving swarm intelligence, which has seen an increase in use in recent years. This synthesis of current and future research will be helpful to research teams working to create an autonomous vehicle with intentions to track, navigate or survey

Security of GPS/INS based On-road Location Tracking Systems

Location information is critical to a wide-variety of navigation and tracking applications. Today, GPS is the de-facto outdoor localization system but has been shown to be vulnerable to signal spoofing attacks. Inertial Navigation Systems (INS) are emerging as a popular complementary system, especially in road transportation systems as they enable improved navigation and tracking as well as offer resilience to wireless signals spoofing, and jamming attacks. In this paper, we evaluate the security guarantees of INS-aided GPS tracking and navigation for road transportation systems. We consider an adversary required to travel from a source location to a destination, and monitored by a INS-aided GPS system. The goal of the adversary is to travel to alternate locations without being detected. We developed and evaluated algorithms that achieve such goal, providing the adversary significant latitude. Our algorithms build a graph model for a given road network and enable us to derive potential destinations an attacker can reach without raising alarms even with the INS-aided GPS tracking and navigation system. The algorithms render the gyroscope and accelerometer sensors useless as they generate road trajectories indistinguishable from plausible paths (both in terms of turn angles and roads curvature). We also designed, built, and demonstrated that the magnetometer can be actively spoofed using a combination of carefully controlled coils. We implemented and evaluated the impact of the attack using both real-world and simulated driving traces in more than 10 cities located around the world. Our evaluations show that it is possible for an attacker to reach destinations that are as far as 30 km away from the true destination without being detected. We also show that it is possible for the adversary to reach almost 60-80% of possible points within the target region in some cities

Motion tracking problems in Internet of Things (IoT) and wireless networking

The dissertation focuses on inferring various motion patterns of internet-of-things (IoT) devices, by leveraging inertial sensors embedded in these objects, as well as wireless signals emitted (or reflected) from them. For instance, we use a combination of GPS signals and inertial sensors on drones to precisely track its 3D orientation over time, ultimately improving safety against failures and crashes. In another application in sports analytics, we embed sensors and radios inside baseballs and cricket balls and compute their 3D trajectory and spin patterns, even when they move at extremely high speeds. In a third application for wireless networks, we explore the possibility of physically moving wireless infrastructure like Access Points and basestations on robots and drones for enhancing the network performance. While these are diverse applications in drones, sports analytics, and wireless networks, the common theme underlying the research is in the development of the core motion-related building blocks. Specifically, we emphasize the philosophy of "fusion of multi modal sensor data with application specific model” as the design principle for building the next generation of diverse IoT applications. To this end, we draw on theoretical techniques in wireless communication, signal processing, and statistics, but translate them to completely functional systems on real-world platforms

Komparasi Akurasi Global Posistion System (GPS) Receiver U-blox Neo-6M dan U-blox Neo-M8N pada Navigasi Quadcopter

Quadcopter UAV development is happening very rapidly. One of the most important in the navigation system is the hardware and software or the used algorithm. Improving the accuracy of Quadcopter positioning is one of the most popular topics in the UAV field. This position parameter is determined by the GPS module. GPS modules produce position and speed information with a high degree of precision, but these modules are vulnerable to interference. Thus, GPS signals are often lost. Moreover, GPS measurements also cannot meet the real-time requirements. Both GPS U-Blox variants, Neo-6M, and M8N become the main problem by testing which are more precise and consistent with the actual geographical position indicated by Google map. Data obtained from GPS receivers are parsed and converted to longitude and latitude coordinates by the ATmega328 IC microcontroller then combine with real-time data from RTC DS1370 and stored continuously in a 2 GB SD card. The transferred geographic coordinate data would be retrieved and converted to CSV format so that it can be plotted into a map. The test was conducted where the Neo-6M GPS receiver was carried ou

Tracking small animals in complex landscapes: a comparison of localisation workflows for automated radio telemetry systems

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