Resilient Communication, Object Classification and Data Fusion in Unmanned Aerial Systems

This paper researches robust data fusion, descriptive reality and control solutions. Cognitive autonomy, vehicle-to-vehicle and vehicle-to-ground communication, as well as wireless hybrid mobile mesh networks are considered. In dynamic and contested environments, the nodes and autonomous swarms must transmit and assess states, evaluate shared data, adapt to dynamic countermeasures, reconfigure, and, ensure secure communication. Robust algorithms and protocols must accomplish data management, perform vulnerability analysis, support data trustworthiness assessment, support physical-virtual reality, and evaluate functionality. Reliability of information sources and communication should be guaranteed despite adversary electronic warfare and disruptive actions. We examine science and technology of communication and data management in distributed processing, control and autonomy applications typifying adversarial environments. Our results ensure sufficient throughput, low latency, robustness, connectivity and secure communication. Topics on target recognition, object classification and dynamic tracking are researched with experimental substantiations.