The ERSA system uses cameras to track aircraft flying too close to the capital’s no-fly zone.

Homeland Protection Systems

Our group performs systems analysis to define challenges to homeland security and develops new systems to solve these challenges. We assess emerging technologies and their abilities to help protect and prevent a threat to the United States, while considering their potential to cause harm if in the wrong hands. These assessments require us to simulate scenarios, conduct physics-based analyses, and evaluate systems in the field. Our analysts and engineers also develop prototype systems, perform demonstrations, and carry out field evaluations of these systems while working closely with our sponsors in the Department of Defense and the Department of Homeland Security, as well as associated end users in the field. These prototype systems address security needs spanning air, land, and maritime border security, critical infrastructure protection, transportation security, disaster response, and support for our forces at home. 

 

Featured Projects

A group of five researchers pose in a field with two UAVs.
We are building a toolbox of autonomous functions for unmanned aerial systems to improve UAS missions and alleviate burden on human operators in the field.
Commercial unmanned aerial systems, like the one pictured above, are increasingly flown in urban areas; if used for illicit purposes, they can pose dangers to civilians.
The prototype is enabling DHS to test technologies that can counter the threats posed by commercial drones.

Advancing Our Research

Events

Mar
15 - 17
Lincoln Laboratory, Lexington, MA

Featured Publications

Radar-optimized wind turbine siting

Jan 1
IEEE Trans. Sustain. Energy, Vol. 13, No. 1, January 2022, pp. 403-13.

Multimodal representation learning via maximization of local mutual information [e-print]

Mar 7
Intl. Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI, 27 September-1 October 2021.

Learning emergent discrete message communication for cooperative reinforcement learning

Feb 24
37th Conf. on Uncertainty in Artificial Intelligence, UAI 2021, early access, 26-30 July 2021.