RESILIENT STATE ESTIMATION FOR MICRO AIR VEHICLES UNDER SENSOR ATTACKS

This thesis proposes a solution to the problem of resilient state estimation and sensor fusion in an autonomous micro air vehicle. The setup comprises of redundant sensors that measure the same physical signal. An adversary may spoof a subset of these sensors and send falsified readings to the controller, potentially compromising performance and safety of the system. This work integrates Brooks-Iyengar Sensor fusion algorithm with a generic state estimator as a method to thwart sensor attacks. The algorithm outputs a point estimate and a fusion interval based on an assumed set of faulty sensors. Finally, the thesis illustrates the usefulness of the resilient state estimator with a case study on a MAV flight dataset.

Department dc:contributor.department

Systems Engineering

Year dc:date.issued

2017

Author dc:creator

• Prasad, Akshay

Advisor dc:contributor.advisor

• Chopra, Nikhil

Language dc:language.iso

en

Identifier

https://doi.org/10.13016/M2KG48

OAI identifier oai:identifier

oai:drum.lib.umd.edu:1903/19557