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Full-Text Articles in Engineering
Cyber-Attack Drone Payload Development And Geolocation Via Directional Antennae, Clint M. Bramlette
Cyber-Attack Drone Payload Development And Geolocation Via Directional Antennae, Clint M. Bramlette
Theses and Dissertations
The increasing capabilities of commercial drones have led to blossoming drone usage in private sector industries ranging from agriculture to mining to cinema. Commercial drones have made amazing improvements in flight time, flight distance, and payload weight. These same features also offer a unique and unprecedented commodity for wireless hackers -- the ability to gain ‘physical’ proximity to a target without personally having to be anywhere near it. This capability is called Remote Physical Proximity (RPP). By their nature, wireless devices are largely susceptible to sniffing and injection attacks, but only if the attacker can interact with the device via …
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Real-Time Path Planning In Constrained, Uncertain Environments, Randall Christensen, Robert C. Leishman
Faculty Publications
A key enabler of autonomous vehicles is the ability to plan the path of the vehicle to accomplish mission objectives. To be robust to realistic environments, path planners must account for uncertainty in the trajectory of the vehicle as well as uncertainty in the location of obstacles. The uncertainty in the trajectory of the vehicle is a difficult quantity to estimate, and is influenced by coupling between the vehicle dynamics, guidance, navigation, and control system as well as any disturbances acting on the vehicle. Monte Carlo analysis is the conventional approach to determine vehicle dispersion, while accounting for the coupled …
First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman
First Approach To Coupling Of Numerical Lifting-Line Theory And Linear Covariance Analysis For Uav State Uncertainty Propagation, Cory D. Goates, Randall S. Christensen, Robert C. Leishman
Faculty Publications
Numerical lifting-line is a computationally efficient method for calculating aerodynamic forces and moments on aircraft. However, its potential has yet to be tapped for use in guidance, navigation, and control (GN&C). Linear covariance analysis is becoming a popular GN&C design tool and shows promise for pairing with numerical lifting-line. Pairing numerical lifting-line with linear covariance analysis allows for forward propagation of state uncertainty for real-time decision making. We demonstrate this for select state variables in a drone aerial recapture situation. Linear covariance analysis uses finite difference derivatives obtained from numerical lifting-line to calculate force and moment variances. These show agreement …