Our goal is to develop optimization algorithms for distributed sensor networks enabling autonomous and dynamic adjustments to problems such as performance issues, jamming, and malicious attacks. Because these networks provide low-profile target detection, classification, and tracking in remote or dangerous areas, enhancing their performance supports a variety of national security missions.
Kailkhura, B., et al. 2017. "Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks." CAMSAP, Curacao, Dutch Antilles, June 2017. LLNL-CONF-731964.
Yen, A. Y., et al. 2018. "Large-Scale Parallel Simulations of Distributed Detection Algorithms for Collaborative Autonomous Sensor Networks." Proc. SPIE Disruptive Technologies in Information Sciences. 10652. doi: 10.1117/12.2306545. LLNL-CONF-749406.